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ORCIDComputer-Aided Diagnosis 2019: San Diego, CA, USA
- Kensaku Mori, Horst K. Hahn:
Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, California, United States, 16-21 February 2019. SPIE Proceedings 10950, SPIE 2019
Breast I
- Joris van Vugt, Elena Marchiori, Ritse Mann, Albert Gubern-Mérida, Nikita Moriakov, Jonas Teuwen:
Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptation. 1095002 - Juhun Lee, Robert M. Nishikawa
:
Detecting mammographically-occult cancer in women with dense breasts using deep convolutional neural network and Radon cumulative distribution transform. 1095003 - Kenny H. Cha, Nicholas Petrick, Aria Pezeshk, Christian G. Graff, Diksha Sharma, Andreu Badal, Aldo Badano, Berkman Sahiner:
Reducing overfitting of a deep learning breast mass detection algorithm in mammography using synthetic images. 1095004 - Kadie Clancy, Lei Zhang, Aly A. Mohamed, Sarah S. Aboutalib, Wendie A. Berg, Shandong Wu:
Deep learning for identifying breast cancer malignancy and false recalls: a robustness study on training strategy. 1095005 - Rachel Anderson, Hui Li, Yu Ji, Peifang Liu, Maryellen L. Giger:
Evaluating deep learning techniques for dynamic contrast-enhanced MRI in the diagnosis of breast cancer. 1095006
Brain
- Ziga Bizjak, Tim Jerman, Bostjan Likar, Franjo Pernus, Aichi Chien, Ziga Spiclin:
Registration based detection and quantification of intracranial aneurysm growth. 1095007 - Mariana P. Bento, Roberto Souza, Marina Salluzzi, Richard Frayne:
Reliability of computer-aided diagnosis tools with multi-center MR datasets: impact of training protocol. 1095008 - Zhe Guo, Ning Guo, Kuang Gong, Quanzheng Li:
Automatic multi-modality segmentation of gross tumor volume for head and neck cancer radiotherapy using 3D U-Net. 1095009 - Bruno Oliveira, Helena R. Torres, Fernando Veloso, Estela Vilhena, Nuno F. Rodrigues, Jaime C. Fonseca, Pedro Morais, João L. Vilaça:
Automatic strategy for extraction of anthropometric measurements for the diagnostic and evaluation of deformational plagiocephaly from infant's head models. 109500A - Ruchika Verma, Ramon Correa, Virginia B. Hill, Niha G. Beig, Abdelkader Mahammedi, Anant Madabhushi, Pallavi Tiwari:
Radiomics of the lesion habitat on pre-treatment MRI predicts response to chemo-radiation therapy in Glioblastoma. 109500B - Samuel Botter Martins, Barbara Caroline Benato, Bruna Ferreira Silva, Clarissa Lyn Yasuda, Alexandre Xavier Falcão:
Modeling normal brain asymmetry in MR images applied to anomaly detection without segmentation and data annotation. 109500C
Breast II
- Bas H. M. van der Velden, Bob D. de Vos, Claudette E. Loo, Hugo J. Kuijf, Ivana Isgum, Kenneth G. A. Gilhuijs:
Response monitoring of breast cancer on DCE-MRI using convolutional neural network-generated seed points and constrained volume growing. 109500D - Yinhao Ren, Rui Hou, Dehan Kong, Yue Geng, Lars J. Grimm, Jeffrey R. Marks, Joseph Y. Lo:
Multiview mammographic mass detection based on a single shot detection system. 109500E - Doiriel Vanegas C., Mahlet A. Birhanu, Nico Karssemeijer, Albert Gubern-Mérida, Michiel Kallenberg:
A deep learning method for volumetric breast density estimation from processed full field digital mammograms. 109500F - Sun Young Park, Dustin Sargent, David Richmond:
Breast density follow-up decision support system using deep convolutional models. 109500G - Peng Zhang, Ming Fan, Yuanzhe Li, Maosheng Xu, Lihua Li:
DCE-MRI based analysis of intratumor heterogeneity by decomposing method for prediction of HER2 status in breast cancer. 109500H
Breast III and Heart
- Seyedehnafiseh Mirniaharikandehei, Morteza Heidari, Gopichandh Danala, Wei Qian, Yuchen Qiu, Bin Zheng:
Association of computer-aided detection results and breast cancer risk. 109500I - Marco Caballo, Jonas Teuwen, Ritse Mann, Ioannis Sechopoulos:
Breast parenchyma analysis and classification for breast masses detection using texture feature descriptors and neural networks in dedicated breast CT images. 109500J - Seong Tae Kim, Jae-Hyeok Lee, Yong Man Ro:
Visual evidence for interpreting diagnostic decision of deep neural network in computer-aided diagnosis. 109500K - Rahul Suresh, Srinivasan Sivanandan, Nitin Singhal, JinYong Lee, Mi-Young Lee, Hye-Sung Won:
Automated measurement of fetal right-myocardial performance index from pulsed wave Doppler spectrum. 109500L - C. Wang, Martin Rajchl, Adrian D. C. Chan, Eranga Ukwatta:
An ensemble of U-Net architecture variants for left atrial segmentation. 109500M - Lambros S. Athanasiou, Max L. Olender, José M. de la Torre Hernandez, Eyal Ben-Assa, Elazer R. Edelman:
A deep learning approach to classify atherosclerosis using intracoronary optical coherence tomography. 109500N
Lung I
- David Chettrit, Orna Bregman-Amitai, Itamar Tamir, Amir Bar, Eldad Elnekave:
PHT-bot: a deep learning based system for automatic risk stratification of COPD patients based upon signs of pulmonary hypertension. 109500O - Ken C. L. Wong, Mehdi Moradi, Joy T. Wu, Tanveer F. Syeda-Mahmood:
Identifying disease-free chest x-ray images with deep transfer learning. 109500P - Ravi K. Samala, Heang-Ping Chan, Caleb Richter, Lubomir M. Hadjiiski, Chuan Zhou, Jun Wei:
Analysis of deep convolutional features for detection of lung nodules in computed tomography. 109500Q - Mohammadhadi Khorrami, Mehdi Alilou, Prateek Prasanna, Pradnya Patil, Pirya Velu, Kaustav Bera, Pingfu Fu, Vamsidhar Velcheti, Anant Madabhushi:
A combination of intra- and peritumoral features on baseline CT scans is associated with overall survival in non-small cell lung cancer patients treated with immune checkpoint inhibitors: a multi-agent multi-site study. 109500R - Sivaramakrishnan Rajaraman, Sema Candemir, George R. Thoma, Sameer K. Antani:
Visualizing and explaining deep learning predictions for pneumonia detection in pediatric chest radiographs. 109500S
Abdomen
- Annika Hänsch, Volker Dicken, Jan Klein, Tomasz Morgas, Benjamin Haas, Horst K. Hahn:
Artifact-driven sampling schemes for robust female pelvis CBCT segmentation using deep learning. 109500T - Clinton J. Wang, Charlie A. Hamm, Brian S. Letzen, James S. Duncan:
A probabilistic approach for interpretable deep learning in liver cancer diagnosis. 109500U - Matias Benitez, James Tian, Mark Kelly, Vignesh Selvakumaran, Matthew Phelan, Maciej A. Mazurowski, Joseph Y. Lo, Geoffrey D. Rubin, Ricardo Henao:
Combining deep learning methods and human knowledge to identify abnormalities in computed tomography (CT) reports. 109500V - Dhanuj Gandikota, Lubomir M. Hadjiiski, Heang-Ping Chan, Kenny H. Cha, Ravi Samala, Elaine M. Caoili, Richard H. Cohan, Alon Z. Weizer, Ajjai Alva, Chintana Paramagul, Jun Wei, Chuan Zhou:
Bladder cancer staging in CT urography: estimation and validation of decision thresholds for a radiomics-based decision support system. 109500W - Guangrui Mu, Yiyi Ma, Miaofei Han, Yiqiang Zhan, Xiang Zhou, Yaozong Gao:
Automatic MR kidney segmentation for autosomal dominant polycystic kidney disease. 109500X - Xiangyuan Ma, Lubomir M. Hadjiiski, Jun Wei, Heang-Ping Chan, Kenny H. Cha, Richard H. Cohan, Elaine M. Caoili, Ravi Samala, Chuan Zhou, Yao Lu:
2D and 3D bladder segmentation using U-Net-based deep-learning. 109500Y
Multiorgan and Colon
- Xiangrong Zhou, Takuya Kojima, Song Wang, Xinxin Zhou, Takeshi Hara, Taiki Nozaki, Masaki Matsusako, Hiroshi Fujita:
Automatic anatomy partitioning of the torso region on CT images by using a deep convolutional network with majority voting. 109500Z - Yang Lei, Yingzi Liu, Xue Dong, Sibo Tian, Tonghe Wang, Xiaojun Jiang, Kristin Higgins, Jonathan J. Beitler, David S. Yu, Tian Liu, Walter J. Curran, Yi Fang, Xiaofeng Yang:
Automatic multi-organ segmentation in thorax CT images using U-Net-GAN. 1095010 - Faisal Mahmood, Ziyun Yang, Richard Chen, Daniel Borders, Wenhao Xu, Nicholas J. Durr:
Polyp segmentation and classification using predicted depth from monocular endoscopy. 1095011 - Thom Scheeve, Ramon-Michel Schreuder, Fons van der Sommen, Joep E. G. IJspeert, Evelien Dekker, Erik J. Schoon, Peter H. N. de With:
Computer-aided classification of colorectal polyps using blue-light and linked-color imaging. 1095012 - Tomoki Uemura, Janne J. Näppi, Huimin Lu, Hyoungseop Kim, Rie Tachibana, Toru Hironaka, Hiroyuki Yoshida:
Ensemble 3D residual network (E3D-ResNet) for reduction of false-positive polyp detections in CT colonography. 1095013 - Weiguo Cao, Marc Jason Pomeroy, Perry J. Pickhardt, Matthew A. Barish, Samuel Stanley III, Zhengrong Liang:
A local geometrical metric-based model for polyp classification. 1095014 - Hayato Itoh, Holger R. Roth, Yuichi Mori, Masashi Misawa, Masahiro Oda, Shin-ei Kudo, Kensaku Mori:
Polyp-size classification with RGB-D features for colonoscopy. 1095015
Lung II
- Erdi Calli, Ecem Sogancioglu, Ernst Th. Scholten, Keelin Murphy, Bram van Ginneken:
Handling label noise through model confidence and uncertainty: application to chest radiograph classification. 1095016 - Ruixiang Tang, Fakrul Islam Tushar, Songyue Han, Rui Hou, Geoffrey D. Rubin, Joseph Y. Lo:
Classification of chest CT using case-level weak supervision. 1095017 - Yuxing Tang, Youbao Tang, Mei Han, Jing Xiao, Ronald M. Summers:
Deep adversarial one-class learning for normal and abnormal chest radiograph classification. 1095018 - Young-Wouk Kim, Sebastián Roberto Tarando, Pierre-Yves Brillet, Catalin I. Fetita:
Image biomarkers for quantitative analysis of idiopathic interstitial pneumonia. 1095019
Radiomics I
- Heather M. Whitney, Yu Ji, Hui Li, Alexandra Edwards, John Papaioannou, Peifang Liu, Maryellen L. Giger:
Effect of diversity of patient population and acquisition systems on the use of radiomics and machine learning for classification of 2, 397 breast lesions. 109501A - Niha G. Beig, Prateek Prasanna, Virginia B. Hill, Ruchika Verma, Vinay Varadan, Anant Madabhushi, Pallavi Tiwari:
Radiogenomic characterization of response to chemo-radiation therapy in glioblastoma is associated with PI3K/AKT/mTOR and apoptosis signaling pathways. 109501B - Sang Ho Lee, Peijin Han, Russell K. Hales, K. Ranh Voong, Todd R. McNutt, Junghoon Lee:
Identifying optimal input using multilevel radiomics and nested cross-validation for predicting pulmonary function in lung cancer patients treated with radiotherapy. 109501C - Ryan Alfano, D. Soetemans, Glenn S. Bauman, Mena Gaed, Madeleine Moussa, Jose A. Gomez, Joseph L. Chin, Stephen E. Pautler, Aaron D. Ward:
Texture-based prostate cancer classification on MRI: how does inter-class size mismatch affect measured system performance? 109501D - Sukanya Iyer, Marwa Ismail, Benita Tamrazi, Ashley Margol, Ruchika Verma, Ramon Correa, Prateek Prasanna, Niha G. Beig, Kaustav Bera, Volodymyr Statsevych, Alexander R. Judkins, Anant Madabhushi, Pallavi Tiwari:
Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI. 109501E - Mehdi Alilou, Pranjal Vaidya, Mohammadhadi Khorrami, Alexia Zagouras, Pradnya Patil, Kaustav Bera, Pingfu Fu, Vamsidhar Velcheti, Anant Madabhushi:
Quantitative vessel tortuosity radiomics on baseline non-contrast lung CT predict response to immunotherapy and are prognostic of overall survival. 109501F
Keynote Session
- Bernardino Romera-Paredes:
The U-net and its impact to medical imaging (Conference Presentation). 109501G
Lung III
- Chenglong Wang, Takayasu Moriya, Yuichiro Hayashi, Holger Roth, Le Lu, Masahiro Oda, Hirotugu Ohkubo, Kensaku Mori:
Weakly-supervised deep learning of interstitial lung disease types on CT images. 109501H - Samuel Berglin, Eura Shin, Jacob Furst, Daniela Raicu:
Efficient learning in computer-aided diagnosis through label propagation. 109501I - Yoshiki Kawata, Noboru Niki, Masahiko Kusumoto, Hironobu Ohmatsu, Keiju Aokage, Genichiro Ishii, Yuji Matsumoto, Takaaki Tsuchida, Kenji Eguchi, Masahiro Kaneko:
Computer-aided CT image features improving the malignant risk prediction in pulmonary nodules suspicious for lung cancer. 109501J - Chufan Gao, Stephen Clark, Jacob Furst, Daniela Raicu:
Augmenting LIDC dataset using 3D generative adversarial networks to improve lung nodule detection. 109501K
Vascular and Radiomics II
- Jiamin Liu, Jianhua Yao, Mohammadhadi Bagheri, Ronald M. Summers:
A semi-supervised CNN learning method with pseudo-class labels for vascular calcification detection on low dose CT scans. 109501L - Joseph J. Foy, Mena Shenouda, Sahar Ramahi, Samuel G. Armato, Daniel T. Ginat:
Variability in radiomics features among iDose reconstruction levels. 109501M - Jingwei Wei, Sirui Fu, Shauitong Zhang, Jie Zhang, Dongsheng Gu, Xiaoqun Li, Xudong Chen, Xiaofeng He, Jianfeng Yan, Ligong Lu, Jie Tian:
Development and validation of a radiomics-based method for macrovascular invasion prediction in hepatocellular carcinoma with prognostic implication. 109501N - Amélé Florence Kouvahe, Catalin I. Fetita:
Efficient detection of vascular structures using locally connected filtering. 109501P
Eyes and New Approaches
- Ziyuan Wang, SriniVas R. Sadda, Zhihong Hu:
Deep learning for automated screening and semantic segmentation of age-related and juvenile atrophic macular degeneration. 109501Q - Mara Graziani, James M. Brown, Vincent Andrearczyk, Veysi Yildiz, J. Peter Campbell, Deniz Erdogmus, Stratis Ioannidis, Michael F. Chiang, Jayashree Kalpathy-Cramer, Henning Müller:
Improved interpretability for computer-aided severity assessment of retinopathy of prematurity. 109501R - Nada Kamona, Qin Li, Benjamin P. Berman, Berkman Sahiner, Nicholas Petrick:
Reproducibility of CT-based texture feature quantification of simulated and 3D-printed trabecular bone: influence of noise and reconstruction kernel. 109501S - Faisal Mahmood, Jeremiah W. Johnson, Ziyun Yang, Nicholas J. Durr:
Fusing attributes predicted via conditional GANs for improved skin lesion classification (Conference Presentation). 109501T - Alexandros Karargyris, Satyananda Kashyap, Joy T. Wu, Arjun Sharma, Mehdi Moradi, Tanveer Fathima Syeda-Mahmood:
Age prediction using a large chest x-ray dataset. 109501U - Mengjie Fang, Di Dong, Ruijia Sun, Li Fan, Yingshi Sun, Shiyuan Liu, Jie Tian:
Using multi-task learning to improve diagnostic performance of convolutional neural networks. 109501V
Radiomics III and Oncology
- Jan Hendrik Moltz:
Stability of radiomic features of liver lesions from manual delineation in CT scans. 109501W - Theo Cleland, James G. Mainprize, Olivier Alonzo-Proulx, Jennifer A. Harvey, Roberta A. Jong, Anne L. Martel, Martin J. Yaffe:
Use of convolutional neural networks to predict risk of masking by mammographic density. 109501X - Thom Scheeve, Maarten R. Struyvenberg, Wouter L. Curvers, Albert J. de Groof, Erik J. Schoon, Jacques J. G. H. M. Bergman, Fons van der Sommen, Peter H. N. de With:
A novel clinical gland feature for detection of early Barrett's neoplasia using volumetric laser endomicroscopy. 109501Y - Shuaitong Zhang, Yafei Qi, Jingwei Wei, Jianxing Niu, Dongsheng Gu, Yuqi Han, Xiaohan Hao, Yali Zang, Jie Tian:
Radiomics analysis potentially reduces over-diagnosis of prostate cancer with PSA levels of 4-10 ng/ml based on DWI data. 109501Z - Ravi K. Samala, Heang-Ping Chan, Lubomir M. Hadjiiski, Chintana Paramagul, Mark A. Helvie, Colleen H. Neal:
Homogenization of breast MRI across imaging centers and feature analysis using unsupervised deep embedding. 1095020
Poster Session: Bone
- Nina Tubau Ribera, Priscille de Dumast, Marilia Yatabe, Antonio C. Ruellas, Marcos Ioshida, Beatriz Paniagua, Martin Styner, João Roberto Gonçalves, Jonas Bianchi, Lucia H. S. Cevidanes, Juan-Carlos Prieto:
Shape variation analyzer: a classifier for temporomandibular joint damaged by osteoarthritis. 1095021 - Jintao Ren, Arash Moaddel H., Ellen M. Hauge, Kresten K. Keller, Rasmus K. Jensen, François Lauze:
Automatic detection and localization of bone erosion in hand HR-pQCT. 1095022 - Jiashi Zhao, Zhengang Jiang, Kensaku Mori, Liyuan Zhang, Wei He, Weili Shi, Yu Miao, Fei Yan, Fei He:
Spinal Vertebrae Segmentation and Localization by Transfer Learning. 1095023 - Keni Zheng, Rachid Jennane, Sokratis Makrogiannis:
Ensembles of sparse classifiers for osteoporosis characterization in digital radiographs. 1095024 - Liyuan Zhang, Jiashi Zhao, Huamin Yang, Weili Shi, Yu Miao, Fei He, Wei He, Yanfang Li, Ke Zhang, Kensaku Mori, Zhengang Jiang:
Multiclass vertebral fracture classification using ensemble probability SVM with multi-feature selection. 1095025
Poster Session: Brain
- Pooneh R. Tabrizi, Awais Mansoor, Rawad Obeid, Anna A. Penn, Marius George Linguraru:
Cranial localization in 2D cranial ultrasound images using deep neural networks. 1095026 - Mina Rezaei, Haojin Yang, Christoph Meinel:
Learning imbalanced semantic segmentation through cross-domain relations of multi-agent generative adversarial networks. 1095027 - Qingfeng Li, Quan Huo, Xiaodan Xing, Yiqiang Zhan, Xiang Sean Zhou, Feng Shi:
Spatial and depth weighted neural network for diagnosis of Alzheimer's disease. 1095028 - Junsik Eom, Hanbyol Jang, Sewon Kim, Jinseong Jang, Dosik Hwang:
Study on discrimination of Alzheimer's disease states using an ensemble neural network's model. 1095029 - Mohammad Mahdi Shiraz Bhurwani, Alexander R. Podgorsak, Anusha Ramesh Chandra, Ryan A. Rava, Kenneth V. Snyder, Elad I. Levy, Jason M. Davies, Adnan H. Siddiqui, Ciprian N. Ionita:
Feasibility study of deep neural networks to classify intracranial aneurysms using angiographic parametric imaging. 109502A - Yuqi Han, Zhen Xie, Yali Zang, Shuaitong Zhang, Dongsheng Gu, Jingwei Wei, Chao Li, Hongyan Chen, Jiang Du, Di Dong, Jie Tian, Dabiao Zhou:
Non-invasive genotype prediction of chromosome 1p/19q co-deletion by development and validation of an MRI-based radiomics signature in lower-grade gliomas. 109502B - Xiaodan Xing, Lili Jin, Feng Shi, Ziwen Peng:
Diagnosis of OCD using functional connectome and Riemann kernel PCA. 109502C
Poster Session: Breast
- Yoon-Chul Kim, Ji-Eun Lee, Inwu Yu, In-Young Baek, Han-Gil Jeong, Beom-Joon Kim, Joon-Kyung Seong, Jong-Won Chung, Oh Young Bang, Woo-Keun Seo:
Evaluation of U-net segmentation models for infarct volume measurement in acute ischemic stroke: comparison with fixed ADC threshold-based methods. 109502D - Xiangyuan Ma, Caleb Fisher, Jun Wei, Mark A. Helvie, Heang-Ping Chan, Chuan Zhou, Lubomir M. Hadjiiski, Yao Lu:
Multi-path deep learning model for automated mammographic density categorization. 109502E - Helder Cesar Rodigues de Oliveira, Carlos F. E. Melo, Juliana H. Catani, Nestor de Barros, Marcelo Andrade da Costa Vieira:
Exploratory learning with convolutional autoencoder for discrimination of architectural distortion in digital mammography. 109502F - Manar N. Mahmoud, Muhammad Ali Rushdi, Iman Ewais, Eman Hosny, Hanan Gewefel, Ahmed M. Mahmoud:
Computationally-efficient wavelet-based characterization of breast tumors using conventional B-mode ultrasound images. 109502G - Linxi Shi, Subashini Srinivasan, Brian A. Hargreaves, Bruce L. Daniel:
Breast dispersion imaging using undersampled rapid dynamic contrast-enhanced MRI. 109502H - Mohammed El Adoui, Mohamed Amine Larhmam, Stylianos Drisis, Mohammed Benjelloun:
Deep Learning approach predicting breast tumor response to neoadjuvant treatment using DCE-MRI volumes acquired before and after chemotherapy. 109502I - Guanxiong Cai, Yanhui Guo, Weiguo Chen, Hui Zeng, Yuanpin Zhou, Yao Lu:
Computer-aided detection and classification of microcalcification clusters on full field digital mammograms using deep convolution neural network. 109502J - Ruvini Navaratna, Aimilia Gastounioti, Meng-Kang Hsieh, Lauren Pantalone, Marie Shelanski, Emily F. Conant, Despina Kontos:
Associations between mammographic phenotypes and histopathologic features in ductal carcinoma in situ. 109502K - Dehan Kong, Yinhao Ren, Rui Hou, Lars J. Grimm, Jeffrey R. Marks, Joseph Y. Lo:
Synthesis and texture manipulation of screening mammograms using conditional generative adversarial network. 109502M - Karen Drukker, Iman El-Bawab, Alexandra Edwards, Christopher Doyle, John Papaioannou, Kirti Kulkarni, Maryellen L. Giger:
Breast MRI radiomics for the pre-treatment prediction of response to neoadjuvant chemotherapy in node-positive breast cancer patients. 109502N - Faranak Aghaei, Alan B. Hollingsworth, Seyedehnafiseh Mirniaharikandehei, Yunzhi Wang, Hong Liu, Bin Zheng:
Developing a new quantitative imaging marker to predict pathological complete response to neoadjuvant chemotherapy. 109502O - Giacomo Nebbia, Aly A. Mohamed, Ruimei Chai, Bingjie Zheng, Margarita L. Zuley, Shandong Wu:
Deep learning of sub-regional breast parenchyma in mammograms for localized breast cancer risk prediction. 109502P - Rui Hou, Yinhao Ren, Lars J. Grimm, Maciej A. Mazurowski, Jeffrey R. Marks, Lorraine M. King, Carlo C. Maley, Eun-Sil Shelley Hwang, Joseph Y. Lo:
Malignant microcalcification clusters detection using unsupervised deep autoencoders. 109502Q - Lei Zhang, Ruimei Chai, Aly A. Mohamed, Bingjie Zheng, Zhimeng Luo, Shandong Wu:
Automated deep-learning method for whole-breast segmentation in diffusion-weighted breast MRI. 109502R - Zhiguo Zhou, Genggeng Qin, Pingkun Yan, Hongxia Hao, Steve B. Jiang, Jing Wang:
A shell and kernel descriptor based joint deep learning model for predicting breast lesion malignancy. 109502S
Poster Session: Cell
- Jianhuo Shen, Teng Li, Chuanrui Hu, Hong He, Jianfei Liu:
Automatic cell segmentation using mini-u-net on fluorescence in situ hybridization images. 109502T
Poster Session: Colon
- Yi Wang, Marc Jason Pomeroy, Weiguo Cao, Yongfeng Gao, Edward Sun, Samuel Stanley III, Zhengrong Liang, Juan Carlos Bucobo:
Polyp classification by Weber's Law as texture descriptor for clinical colonoscopy. 109502V - Marc Jason Pomeroy, Almas F. Abbasi, Kevin Baker, Matthew A. Barish, Samuel Stanley III, Kenneth Ng, Perry J. Pickhardt, Zhengrong Liang:
Improved polyp classification by inclusion of the surrounding colon wall textures. 109502W - Hainan Sang, Jiang Meng, Yang Liu, Zhengrong Liang, Hongbing Lu:
The detection of non-polypoid colorectal lesions using the texture feature extracted from intact colon wall: a pilot study. 109502X - Yi Wang, Marc Jason Pomeroy, Weiguo Cao, Yongfeng Gao, Edward Sun, Samuel Stanley III, Juan Carlos Bucobo, Zhengrong Liang:
Differentiation of polyps by clinical colonoscopy via integrated color information, image derivatives and machine learning. 109502Y
Poster Session: Eyes
- Supriti Mulay, Keerthi Ram, Mohanasankar Sivaprakasam, Anand Vinekar:
Early detection of retinopathy of prematurity stage using deep learning approach. 109502Z - Jianfei Liu, Haewon Jung, Tao Liu, Johnny Tam:
Longitudinal matching of in vivo adaptive optics images of fluorescent cells in the human eye using stochastically consistent superpixels. 1095030 - Vinayak Joshi, Jeffrey Wigdahl, Jeremy Benson, Sheila C. Nemeth, Peter Soliz:
Computer-based detection of age-related macular degeneration and glaucoma using retinal images and clinical data. 1095031 - Fatemeh Zabihollahy, Eranga Ukwatta:
Fully-automated segmentation of optic disk from retinal images using deep learning techniques. 1095032
Poster Session: Head
- Helena R. Torres, Bruno Oliveira, Fernando Veloso, Mario Ruediger, Wolfram Burkhardt, António H. J. Moreira, Nuno Dias, Pedro Morais, Jaime C. Fonseca, João L. Vilaça:
Deep learning-based detection of anthropometric landmarks in 3D infants head models. 1095034 - Liyun Tu, Antonio R. Porras, Albert Oh, Natasha Leporé, Graham C. Buck, Deki Tsering, Andinet Enquobahrie, Robert T. Keating, Gary F. Rogers, Marius George Linguraru:
Quantitative evaluation of local head malformations from 3 dimensional photography: application to craniosynostosis. 1095035 - Manuel Berger, Martin Pillei, Andreas H. Mehrle, Wolfgang Recheis, Florian Kral, Michael Kraxner, Wolfgang Freysinger:
Predicting resection volumes within the nasal cavity to improve patients breathing. 1095036
Poster Session: Heart
- Luke Chaplin, Tim Cootes:
Automated scoring of aortic calcification in vertebral fracture assessment images. 1095038 - Jordan D. Fuhrman, Jennie Crosby, Rowena Yip, Claudia I. Henschke, David F. Yankelevitz, Maryellen L. Giger:
Detection and classification of coronary artery calcifications in low dose thoracic CT using deep learning. 1095039 - Noriyuki Takahashi, Yuki Shinohara, Toshibumi Kinoshita, Tomomi Ohmura, Keisuke Matsubara, Yongbum Lee, Hideto Toyoshima:
Computerized identification of early ischemic changes in acute stroke in noncontrast CT using deep learning. 109503A - Fatemeh Zabihollahy, James A. White, Eranga Ukwatta:
Fully automated segmentation of left ventricular myocardium from 3D late gadolinium enhancement magnetic resonance images using a U-net convolutional neural network-based model. 109503C
Poster Session: Kidneys
- Eric Wu, Lubomir M. Hadjiiski, Ravi K. Samala, Heang-Ping Chan, Kenny H. Cha, Caleb Richter, Richard H. Cohan, Elaine M. Caoili, Chintana Paramagul, Ajjai Alva, Alon Z. Weizer:
Deep learning based bladder cancer treatment response assessment. 109503D
Poster Session: Liver
- Alex Treacher, Daniel Beauchamp, Bilal Quadri, David Fetzer, Abhinav Vij, Takeshi Yokoo, Albert Montillo:
Deep learning convolutional neural networks for the estimation of liver fibrosis severity from ultrasound texture. 109503E
Poster Session: Lung
- Adora M. DSouza, Anas Z. Abidin, Axel Wismüller:
Automated identification of thoracic pathology from chest radiographs with enhanced training pipeline. 109503F - Atsushi Yaguchi, Kota Aoyagi, Akiyuki Tanizawa, Yoshiharu Ohno:
3D fully convolutional network-based segmentation of lung nodules in CT images with a clinically inspired data synthesis method. 109503G - Guillaume Vanoost, Yashin Dicente Cid, Daniel L. Rubin, Adrien Depeursinge:
A lung graph model for the classification of interstitial lung diseases on CT images. 109503H - Oliver Weinheimer, Mark Oliver Wielpütz, Philip Konietzke, Claus Peter Heussel, Hans-Ulrich Kauczor, Terry E. Robinson, Craig J. Galbán:
Improving pulmonary lobe segmentation on expiratory CTs by using aligned inspiratory CTs. 109503I - Eyjolfur Gudmundsson, Christopher M. Straus, Samuel G. Armato:
Pre-trained deep convolutional neural networks for the segmentation of malignant pleural mesothelioma tumor on CT scans. 109503J - Satyananda Kashyap, Mehdi Moradi, Alexandros Karargyris, Joy T. Wu, Michael Morris, Babak Saboury, Eliot L. Siegel, Tanveer F. Syeda-Mahmood:
Artificial intelligence for point of care radiograph quality assessment. 109503K - Maysa M. G. Macedo, Dário A. B. Oliveira:
Exploring features towards semantic characterization of lung nodules in computed tomography images. 109503L - Yuki Kitahara, Rie Tanaka, Holger R. Roth, Hirohisa Oda, Kensaku Mori, Kazuo Kasahara, Isao Matsumoto:
Lung segmentation based on a deep learning approach for dynamic chest radiography. 109503M - Devanshu Agrawal, Hong-Jun Yoon, Georgia D. Tourassi, Jacob D. Hinkle:
Computer-aided detection using non-convolutional neural network Gaussian processes. 109503N - Yue Geng, Yinhao Ren, Rui Hou, Songyue Han, Geoffrey D. Rubin, Joseph Y. Lo:
2.5D CNN model for detecting lung disease using weak supervision. 109503O - Mark Loyman, Hayit Greenspan:
Lung nodule retrieval using semantic similarity estimates. 109503P - Fangfang Han, Linkai Yan, Chen Li, Shouliang Qi, William Moore, Zhengrong Liang, Wei Qian:
Predicting unnecessary nodule biopsy for a small lung cancer screening dataset by less-abstractive deep features. 109503Q - Mohammadreza Negahdar, David Beymer:
Lung tissue characterization for emphysema differential diagnosis using deep convolutional neural networks. 109503R - Xinzhuo Zhao, Wenqing Sun, Wei Qian, Shouliang Qi, Jianjun Sun, Bo Zhang, Zhigang Yang:
Fine-grained lung nodule segmentation with pyramid deconvolutional neural network. 109503S - Yasutaka Moriwaki, Nobuhiro Miyazaki, Hiroaki Takebe, Takayuki Baba, Hiroaki Terada, Toru Higaki, Kazuo Awai, Machiko Nakagawa, Akio Ozawa, Kennji Kitayama, Yasuharu Ogino:
Similar CT image retrieval method based on lesion nature and their three-dimensional distribution. 109503T
Poster Session: Lymph Nodes and Thyroid
- Keisuke Bando, Ren Nishimoto, Mikio Matsuhiro, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Gen Iinuma:
Metastatic lymph node analysis of colorectal cancer using quadruple-phase CT images. 109503U - Youbao Tang, Sooyoun Oh, Yuxing Tang, Jing Xiao, Ronald M. Summers:
CT-realistic data augmentation using generative adversarial network for robust lymph node segmentation. 109503V - Kamal Jnawali, Bhargava Chinni, Vikram Dogra, Navalgund Rao:
Transfer learning for automatic cancer tissue detection using multispectral photoacoustic imaging. 109503W
Poster Session: Prostate
- Bo Wang, Yang Lei, Jiwoong Jason Jeong, Tonghe Wang, Yingzi Liu, Sibo Tian, Pretesh Patel, Xiaojun Jiang, Ashesh B. Jani, Hui Mao, Walter J. Curran, Tian Liu, Xiaofeng Yang:
Automatic MRI prostate segmentation using 3D deeply supervised FCN with concatenated atrous convolution. 109503X - Lin Li, Rakesh Shiradkar, Ahmad Algohary, Patrick Leo, Cristina Magi-Galluzzi, Eric Klein, Andrei S. Purysko, Anant Madabhushi:
Radiomic features derived from pre-operative multi-parametric MRI of prostate cancer are associated with Decipher risk score. 109503Y
Poster Session: Radiomics
- Rahul Paul, Dmitry Cherezov, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof:
Towards deep radiomics: nodule malignancy prediction using CNNs on feature images. 109503Z - Shou Wang, Xi Chen, Zhenyu Liu, Qingxia Wu, Yongbei Zhu, Meiyun Wang, Jie Tian:
Radiomics analysis on T2-MR image to predict lymphovascular space invasion in cervical cancer. 1095040 - Kayla R. Mendel, Hui Li, Nabihah Tayob, Randa El-Zein, Isabelle Bedrosian, Maryellen L. Giger:
Temporal mammographic registration for evaluation of architecture changes in cancer risk assessment. 1095041 - Farzad Khalvati, Yucheng Zhang, Phuong H. U. Le, Isha Gujrathi, Masoom A. Haider:
PI-RADS guided discovery radiomics for characterization of prostate lesions with diffusion-weighted MRI. 1095042 - Saima Rathore, Hamed Akbari, Spyridon Bakas, Jared Pisapia, Xiao Da, Donald M. O'Rourke, Christos Davatzikos:
Non-invasive transcriptomic classification of de novo Glioblastoma patients through multivariate quantitative analysis of baseline preoperative multimodal magnetic resonance imaging. 1095043 - Qinmei Li, James D. Dormer, Priyanka Daryani, Deji Chen, Zhenfeng Zhang, Baowei Fei:
Radiomics analysis of MRI for predicting molecular subtypes of breast cancer in young women. 1095044 - Michael G. Wels, Félix Lades, Alexander Muehlberg, Michael Sühling:
General purpose radiomics for multi-modal clinical research. 1095046 - Chuan Zhou, Qian Dong, Heang-Ping Chan, Erica L. Campagnaro, Jun Wei, Lubomir M. Hadjiiski:
Quantitative MRI biomarker for treatment response assessment of multiple myeloma: robustness evaluation using independent test set of prospective cases. 1095047 - Ge Cui, Jiwoong Jason Jeong, Yang Lei, Tonghe Wang, Tian Liu, Walter J. Curran, Hui Mao, Xiaofeng Yang:
Machine-learning-based classification of Glioblastoma using MRI-based radiomic features. 1095048 - Zeina A. Shboul, Khan M. Iftekharuddin:
Prediction of low-grade glioma progression using MR imaging. 1095049 - Qiyuan Hu, Heather M. Whitney, Alexandra Edwards, John Papaioannou, Maryellen L. Giger:
Radiomics and deep learning of diffusion-weighted MRI in the diagnosis of breast cancer. 109504A
Poster Session: Skin
- Joanna Jaworek-Korjakowska:
Acral melanocytic lesion segmentation with a convolution neural network (U-Net). 109504B
Poster Session: Staging
- P. P. J. H. Langenhuizen, Hans Van Gorp, Sveta Zinger, Jeroen Verheul, Sieger Leenstra, Peter H. N. de With:
Dose distribution as outcome predictor for Gamma Knife radiosurgery on vestibular schwannoma. 109504C
Poster Session: Vascular
- Tonghe Wang, Yang Lei, Ghazal Shafai-Erfani, Xiaojun Jiang, Xue Dong, Jun Zhou, Tian Liu, Walter J. Curran, Xiaofeng Yang, Hui-Kuo Shu:
Learning-based automatic segmentation on arteriovenous malformations from contract-enhanced CT images. 109504D - Alexander R. Podgorsak, Mohammad Mahdi Bhurwani, Ryan A. Rava, Anusha Ramesh Chandra, Ciprian N. Ionita:
Use of a convolutional neural network for aneurysm identification in digital subtraction angiography. 109504E - Ran Zhou, Wei Ma, Aaron Fenster, Mingyue Ding:
U-Net based automatic carotid plaque segmentation from 3D ultrasound images. 109504F
Poster Session: New Approaches
- Chaitanya Kolluru, Beth A. Benetz, Naomi Joseph, Harry J. Menegay, Jonathan H. Lass, David L. Wilson:
Machine learning for segmenting cells in corneal endothelium images. 109504G - Songyue Han, James Tian, Mark Kelly, Vignesh Selvakumaran, Ricardo Henao, Geoffrey D. Rubin, Joseph Y. Lo:
Classifying abnormalities in computed tomography radiology reports with rule-based and natural language processing models. 109504H - Mafalda Couto, João Gomes Fonseca, António H. J. Moreira, Tiago Henriques-Coelho, Jaime C. Fonseca, António C. M. Pinho, Jorge Correia-Pinto, João L. Vilaça:
Patient-specific outcome simulation after surgical correction of Pectus Excavatum: a preliminary study. 109504I
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