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ORCID20th ISBI 2023: Cartagena, Colombia
- 20th IEEE International Symposium on Biomedical Imaging, ISBI 2023, Cartagena, Colombia, April 18-21, 2023. IEEE 2023, ISBN 978-1-6654-7358-3
- Keita Takeda, Eiji Mitate, Tomoya Sakai:
Background Subtraction Approach to Unsupervised Cell Segmentation: Toward Excluding Spurious Features in Degraded Cytology Slides. 1-5 - Alexander Ziller, Ayhan Can Erdur, Friederike Jungmann
, Daniel Rueckert, Rickmer Braren, Georgios Kaissis:
Exploiting Segmentation Labels and Representation Learning to Forecast Therapy Response of PDAC Patients. 1-5 - Jiesi Hu, Yanwu Yang, Xutao Guo, Bo Peng, Hua Huang, Ting Ma:
DECOR-Net: A Covid-19 Lung Infection Segmentation Network Improved by Emphasizing Low-Level Features and Decorrelating Features. 1-5 - Yousuf Babiker M. Osman, Cheng Li, Weijian Huang, Nazik Elsayed, Leslie Ying, Hairong Zheng, Shanshan Wang:
Semi-Supervised and Self-Supervised Collaborative Learning for Prostate 3D MR Image Segmentation. 1-4 - Alexandre Stenger, Luc Vedrenne, Patrick Schultz, Sylvain Faisan, Étienne Baudrier, Benoît Naegel:
Fast and Interpretable Unsupervised Domain Adaptation for FIB-SEM Cell Segmentation. 1-5 - Ahmad Chaddad, Yousef Katib, Camel Tanougast:
Advances in MRI-Based Radiomics for Prostate Cancer. 1-5 - Difei Gu, Dexu Wang, Xiaofan Zhang, Hongsheng Li:
Semi-Supervised Pulmonary Airway Segmentation with Two-Stage Feature Specialization Mechanism. 1-5 - Sanjay Ghosh, Chang Cai, Yijing Gao, Ali Hashemi, Stefan Haufe, Kensuke Sekihara, Ashish Raj, Srikantan S. Nagarajan:
Bayesian Inference for Brain Source Imaging with Joint Estimation of Structured Low-Rank Noise. 1-5 - Arthur Longuefosse, Gaël Dournes, Ilyes Benlala, Baudouin Denis de Senneville, François Laurent, Pascal Desbarats, Fabien Baldacci:
Lung CT Synthesis Using GANs with Conditional Normalization on Registered Ultrashort Echo-Time MRI. 1-5 - SeokHwan Oh, Myeong-Gee Kim, Young-Min Kim, Guil Jung, Hyuksool Kwon, Hyeon-Min Bae:
Spatio-Temporal Quantitative Ultrasound Imaging for Breast Cancer Identification. 1-5 - Filip Rusak, Rodrigo Santa Cruz, Hilda Chourak, Elliot Smith, Jurgen Fripp, Clinton Fookes, Pierrick Bourgeat, Andrew P. Bradley:
When to Use Augmentation - Variability Insufficient for Cortical Thickness Estimation Improvement. 1-5 - Verena Jasmin Hallitschke, Tobias Schlumberger, Philipp Kataliakos, Zdravko Marinov, Moon Kim, Lars Heiliger, Constantin Seibold, Jens Kleesiek, Rainer Stiefelhagen:
Multimodal Interactive Lung Lesion Segmentation: A Framework for Annotating PET/CT Images Based on Physiological and Anatomical Cues. 1-5 - Rui Hu, Jianan Cui, Chengjin Yu, Yunmei Chen, Huafeng Liu:
STPDnet: Spatial-Temporal Convolutional Primal Dual Network for Dynamic Pet Image Reconstruction. 1-5 - Nabil Vindas, Nicole Labra Avila, Fan Zhang, Tengfei Xue, Lauren J. O'Donnell, Jean-François Mangin:
GeoLab: Geometry-Based Tractography Parcellation of Superficial White Matter. 1-5 - Ehsan Khodapanah Aghdam, Reza Azad, Maral Zarvani, Dorit Merhof:
Attention Swin U-Net: Cross-Contextual Attention Mechanism for Skin Lesion Segmentation. 1-5 - Ahmad Chaddad, Yousef Katib, Camel Tanougast:
A One-Dimensional Convolutional Neural Network Model for Predicting the Survival Outcome of Coronavirus Disease 2019. 1-4 - Thibault Sauron, Carole Lazarus, Camille Kurtz, Florence Cloppet:
Learning Representations for MR Image Retrieval: Contrastive Models Versus Other Supervision Strategies. 1-5 - Matthew McCumber, Kevin Tyner, Srijita Das, William C. Stacey, Garnett C. Smith, Mustaffa Alfatlawi, Stephen V. Gliske:
Seizure Onset Localization From Ictal Intracranial EEG Data Using Online Dynamic Mode Decomposition. 1-4 - Zongyu Li, Yucong Lin, Danni Ai, Jian Yang:
A Global-Local Features Exchange and Fusion Network for Multi-Organ Segmentation. 1-5 - Sharif Amit Kamran, Khondker Fariha Hossain, Alireza Tavakkoli, George Bebis, Salah A. Baker:
Swin-SFTNet : Spatial Feature Expansion and Aggregation Using Swin Transformer for Whole Breast Micro-Mass Segmentation. 1-5 - Mohammad Sadegh Nasr, Amir Hajighasemi, Paul Koomey, Parisa Boodaghi Malidarreh, Michael Robben, Jillur Rahman Saurav, Helen H. Shang, Manfred Huber, Jacob M. Luber:
Clinically Relevant Latent Space Embedding of Cancer Histopathology Slides Through Variational Autoencoder based Image Compression. 1-5 - Haoran Li, Cheng Li, Weijian Huang, Xiawu Zheng, Yan Xi, Shanshan Wang:
Digest: Deeply Supervised Knowledge Transfer Network Learning for Brain Tumor Segmentation with Incomplete Multi-Modal MRI Scans. 1-4 - Dan Segev, Ronen Basri, Tomer Batash, Itay Chowers, Daniel Harari, Rivkah Lender, Jaime Levi, Yahel Shwartz, Liran Tiosano, Shimon Ullman, Meirav Galun:
Attention Based Multi-Label Classification of Diabetic Retinopathy from Optical Coherence Tomography. 1-5 - Kai Packhäuser, Lukas Folle, Florian Thamm, Andreas Maier:
Generation of Anonymous Chest Radiographs Using Latent Diffusion Models for Training Thoracic Abnormality Classification Systems. 1-5 - Armin Iraji, Katarzyna Kazimierczak, Jiayu Chen, Sara Motlaghian, Karsten Specht, Tülay Adali, Vince D. Calhoun:
The Nonlinear Brain: Towards Uncovering Hidden Brain Networks Using Explicitly Nonlinear Functional Interaction. 1-4 - Hanying Liang, Guochen Ning, Xinran Zhang, Hongen Liao:
Semi-supervised Anatomy Tracking with Contrastive Representation Learning in Ultrasound Sequences. 1-5 - Seonghui Min, Won-Ki Jeong:
CGAM: Click-Guided Attention Module for Interactive Pathology Image Segmentation via Backpropagating Refinement. 1-5 - Pablo Toledo Margalef, Pablo Navarro, Tábita Hünemeier, Alexandre C. Pereira, Rolando González-José, Claudio Delrieux:
Deep Learning Based UV Facial Imaging Generation. 1-5 - Nicolas Pinon, Geoffroy Oudoumanessah, Robin Trombetta, Michel Dojat, Florence Forbes, Carole Lartizien:
Brain Subtle Anomaly Detection Based on Auto-Encoders Latent Space Analysis: Application To De Novo Parkinson Patients. 1-5 - Valentina Vadori, Jean-Marie Graïc, Livio Finos, Livio Corain, Antonella Peruffo, Enrico Grisan:
Mr-Nom: Multi-Scale Resolution of Neuronal Cells in Nissl-Stained Histological Slices Via Deliberate over-Segmentation and Merging. 1-5 - Zhishan Jiang, Ke Yan, Le Lu, Minfeng Xu:
Div-Attention: A Plug-and-Play Module for 3D Medical Image Segmentation. 1-4 - Nicolas Portal, Nadjia Kachenoura, Thomas Dietenbeck, Catherine Achard:
SFB-net for Cardiac Segmentation: Bridging the Semantic Gap with Attention. 1-5 - Nikhil J. Dhinagar, Conor Owens-Walton, Emily Laltoo, Christina P. Boyle, Yao-Liang Chen, Philip A. Cook, Corey McMillan, Chih-Chien Tsai, Jiun-Jie Wang, Yih-Ru Wu, Ysbrand D. van der Werf, Paul M. Thompson:
Curriculum Based Multi-Task Learning for Parkinson's Disease Detection. 1-5 - Gregory Holste, Douwe van der Wal, Hans Pinckaers, Rikiya Yamashita, Akinori Mitani, Andre Esteva:
Improved Multimodal Fusion for Small Datasets with Auxiliary Supervision. 1-5 - Yadan Li, Mohammad Ali Armin, Simon Denman, David Ahmedt-Aristizabal:
Automated Coronary Arteries Labeling Via Geometric Deep Learning. 1-5 - Qingqing Guo, Xianyong Fang, Linbo Wang, Enming Zhang, Zhengyi Liu:
LGANet: Local-Global Augmentation Network for Skin Lesion Segmentation. 1-5 - Xiaoqing Liu, Kengo Araki, Shota Harada, Akihiko Yoshizawa, Kazuhiro Terada, Mariyo Kurata, Naoki Nakajima, Hiroyuki Abe, Tetsuo Ushiku, Ryoma Bise:
Cluster Entropy: Active Domain Adaptation in Pathological Image Segmentation. 1-5 - Xinwen Zhang, Chaoyi Zhang, Dongnan Liu, Qianbi Yu, Weidong Cai:
SynthMix: Mixing Up Aligned Synthesis for Medical Cross-Modality Domain Adaptation. 1-5 - Weinan Song, Gaurav Fotedar, Nima Tajbakhsh, Ziheng Zhou, Lei He, Xiaowei Ding:
MDT-Net: Multi-Domain Transfer by Perceptual Supervision for Unpaired Images in OCT Scan. 1-5 - Ananya Jana, Ramanathan Arunachalam, Carlos D. Minacapelli, Kaitlyn Catalano, Carlos Catalano, Vinod Rustgi, Dimitris N. Metaxas:
Scale-Aware Multi-Instance Learning for Early Prognosis of Subjects at Risk of Developing Hepatocellular Carcinoma. 1-5 - Alvaro Fernandez-Quilez, Linas Vidziunas, Ørjan Kløvfjell Thoresen, Ketil Oppedal, Svein Reidar Kjosavik, Trygve Eftestøl:
Out-of-Distribution Multi-view auto-Encoders for Prostate Cancer Lesion Detection. 1-5 - Amine Sadikine, Bogdan Badic, Jean-Pierre Tasu, Vincent Noblet, Pascal Ballet, Dimitris Visvikis, Pierre-Henri Conze:
Scale-Specific Auxiliary Multi-Task Contrastive Learning for Deep Liver Vessel Segmentation. 1-5 - Won-Dong Jang, Stanislav Lukyanenko, Donglai Wei, Jiancheng Yang, Brian D. Leahy, Helen Y. Yang, Dalit Ben-Yosef, Daniel Needleman, Hanspeter Pfister:
Multi-Task Curriculum Learning for Partially Labeled Data. 1-5 - Jiangjie Wu, Lixuan Chen, Zhenghao Li, Lihui Wang, Rongpin Wang, Hongjiang Wei, Yuyao Zhang:
ASSURED: A Self-Supervised Deep Decoder Network for Fetus Brain MRI Reconstruction. 1-5 - Leonhard Rist, Oliver Taubmann, Alexander Mühlberg, Felix Denzinger, Florian Thamm, Michael Sühling, Dominik Nörenberg, Julian Walter Holch, Stefan Maurus, Leonie Gebauer, Thomas Huber, Andreas Maier:
Spatial Lesion Graphs: Analyzing Liver Metastases with Geometric Deep Learning for Cancer Survival Regression. 1-5 - Tochi Oguguo, Ghada Zamzmi, Sivaramakrishnan Rajaraman, Feng Yang, Zhiyun Xue, Sameer K. Antani:
A Comparative Study of Fairness in Medical Machine Learning. 1-5 - Kuaikuai Duan, Rogers F. Silva, Jingyu Liu, Oktay Agcaoglu, Vince D. Calhoun:
Any-Way Independent Component Analysis with Reference. 1-4 - Yu Fu, Yanyan Huang, Shunjie Dong, Yalin Wang, Tianbai Yu, Meng Niu, Cheng Zhuo:
SFCNEXT: A Simple Fully Convolutional Network for Effective Brain Age Estimation with Small Sample Size. 1-5 - Yuxuan Zhang, Qingzhong Wang, Jiang Bian, Yi Liu, Yanwu Xu, Dejing Dou, Haoyi Xiong:
Video4MRI: An Empirical Study on Brain Magnetic Resonance Image Analytics with CNN-Based Video Classification Frameworks. 1-5 - Kit Mills Bransby, Vincenzo Tufaro, Murat Çap, Greg G. Slabaugh, Christos Bourantas, Qianni Zhang:
3D Coronary Vessel Reconstruction from Bi-Plane Angiography Using Graph Convolutional Networks. 1-5 - David Olivier, Michael J. McGuffin, Catherine Laporte:
Utilizing Sonographer Visual Attention for Probe Movement Guidance in Cardiac Point of Care Ultrasound. 1-5 - Ye Tian, Geoffrey Wu, Srilaxmi Bearelly, Andrew Laine, Kaveri A. Thakoor, Liat Shenhav:
DVT-Net: A Multimodal Deep Vascular Topology Network for Disease Prediction. 1-5 - Derui Li, Yan Hu, Junyong Shen, Luoying Hao, Jiang Liu:
Semi-Supervised Surgical Video Semantic Segmentation with Cross Supervision of Inter-Frame. 1-5 - Andrew Stamper, Abhinav Singh, James McCouat, Irina Voiculescu:
Infant Hip Screening Using Multi-Class Ultrasound Scan Segmentation. 1-4 - Xuetong Wang, Rong Zhou, Kanhao Zhao, Alex D. Leow, Yu Zhang, Lifang He:
Normative Modeling Via Conditional Variational Autoencoder and Adversarial Learning to Identify Brain Dysfunction in Alzheimer's Disease. 1-4 - Yejia Zhang, Pengfei Gu, Nishchal Sapkota, Hao Zheng, Peixian Liang, Danny Z. Chen:
A Point in the Right Direction: Vector Prediction for Spatially-Aware Self-Supervised Volumetric Representation Learning. 1-5 - Dipayan Dewan, Anupam Borthakur, Debdoot Sheet:
Attention in a Little Network is All You Need to Go Green. 1-4 - Patty Coupeau, Jean-Baptiste Fasquel, Josselin Demas, Lucie Hertz-Pannier, Mickaël Dinomais:
Detecting Cerebral Palsy in Neonatal Stroke Children: GNN-Based Detection Considering the Structural Organization of Basal Ganglia. 1-4 - Jeff L. Rhoades, Arlo Sheridan, Mukul Narwani, Brian Reicher, Mark Larson, Shuhan Xie, Tri Nguyen, Aaron T. Kuan, Alexandra Pacureanu, Wei-Chung Allen Lee, Jan Funke:
Unpaired Image Enhancement for Neurite Segmentation in x-ray Tomography. 1-5 - Yang Qin, Liting Wang, Lei Guo, Junwei Han, Xintao Hu:
Selective Visual Attention Revealed by Integrating FMRI and Eye-Tracking. 1-5 - Qiang Liu, Jun Shi, Liang Qiao, Ziqi Zhu, Hong An, Minfan Zhao:
FRNET: An Effective Hybrid Structure for Automatic Segmentation of Head and Neck Primary Tumors from Multimodal Images. 1-5 - Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun:
Identifying Neuropsychiatric Disorder Subtypes and Subtype-Dependent Variation in Diagnostic Deep Learning Classifier Performance. 1-4 - Yuda Bi, Anees Abrol, Zening Fu, Vince D. Calhoun:
MultiViT: Multimodal Vision Transformer for Schizophrenia Prediction using Structural MRI and Functional Network Connectivity Data. 1-5 - William Trung Le, Chulmin Bang, Philippine Cordelle, Daniel Markel, Phuc Felix Nguyen-Tan, Houda Bahig, Samuel Kadoury:
Prediction of Head and Neck Radiotherapy Toxicity Using a Deformable 3D CNN on Longitudinal Daily CBCT Acquisitions. 1-5 - Suemin Jeon, Kanggeun Lee, Won-Ki Jeong:
Undersampled MRI Reconstruction Using Switchable Interdependent Self-Cooperative Learning Without Paired Training Data. 1-5 - Sifan Song, Jinfeng Wang, Fengrui Cheng, Qirui Cao, Yihan Zuo, Yongteng Lei, Ruomai Yang, Chunxiao Yang, Frans Coenen, Jia Meng, Kang Dang, Jionglong Su:
A Robust Framework of Chromosome Straightening With Vit-Patch Gan. 1-5 - Moxin Zhao, Nan Meng, Jason Pui Yin Cheung, Teng Zhang:
PCT-GAN: A Real CT Image Super-Resolution Model for Trabecular Bone Restoration. 1-5 - Yanzhou Su, Changjian Deng, Zhongying Deng, Jin Ye, Junjun He, Jian Cheng:
Go To The Right: A Real-Time and Accurate Polyp Segmentation Model for Practical Use. 1-5 - Xiaozhao Liu, Mianxin Liu, Lang Mei, Yuyao Zhang, Feng Shi, Han Zhang, Dinggang Shen:
Mining Fmri Dynamics with Parcellation Prior for Brain Disease Diagnosis. 1-5 - Roman Spilger, Ji Young Lee, Minh Tu Pham, Ralf Bartenschlager, Karl Rohr:
Deep Learning Method for Probabilistic Particle Detection and Tracking in Fluorescence Microscopy Images. 1-4 - Minhui Tang, Yu Fang, Lei Ma, Yu Zhang, Zhiming Cui, Dinggang Shen:
Dental Anatomy Segmentation from Cone Beam CT Images. 1-4 - Yekta Kesenci, Aleix Boquet-Pujadas, Michael Unser, Jean-Christophe Olivo-Marin:
Probing Intracellular Elasticity with Minimal-Hessian Registration. 1-5 - Mehdi Shekarnabi, Touria Ahaouari, Jean-Christophe Richard, Sam Bayat, Maciej Orkisz:
CT Registration-Derived Biomarkers of Recruitability in Ards. 1-5 - Yuhan Zhang, Ziqi Tang, Dawei Yang, An-ran Ran, Carol Y. Cheung, Pheng-Ann Heng:
LVCL: Label-Volume Contrastive Learning for Multi-Label Classification of Retinal Oct Volumes. 1-5 - Mathieu Leclercq, Antonio C. Ruellas, Marcela Gurgel, Marilia Yatabe, Jonas Bianchi, Lucia H. S. Cevidanes, Martin Styner, Beatriz Paniagua, Juan Carlos Prieto:
Dentalmodelseg: Fully Automated Segmentation of Upper and Lower 3D Intra-Oral Surfaces. 1-5 - Shengyuan Liu, Mengjie Fang, Di Dong, Wenting Shang, Jie Tian:
Multi-task Residual Cross-attention Network for Tumor Segmentation and Lymph Node Metastasis Prediction in Cervical Cancer. 1-5 - Jana Osstyn, Femke Danckaers, Annemieke Van Haver, José Oramas, Matthias Vanhees, Jan Sijbers:
Automated Virtual Reduction of Displaced Distal Radius Fractures. 1-4 - Yihan Wu, Ali Gholipour, Lana Vasung, Davood Karimi:
A Computational Framework for Characterizing Normative Development of Structural Brain Connectivity in the Perinatal Stage. 1-5 - Rosana El Jurdi, Olivier Colliot:
How Precise are Performance Estimates for Typical Medical Image Segmentation Tasks? 1-5 - Priscille de Dumast, Meritxell Bach Cuadra:
Domain Generalization in Fetal Brain MRI Segmentation with Multi-Reconstruction Augmentation. 1-5 - Hari Om Aggrawal, Dipam Goswami, Vinti Agarwal:
Bounding Box Priors for Cell Detection with Point Annotations. 1-4 - Lanhong Yao, Zheyuan Zhang, Ulas Bagci:
Ensemble Learning with Residual Transformer for Brain Tumor Segmentation. 1-5 - Ligang Fan, Yun Bian, Weifang Zhu, Fei Shi, Xinjian Chen, Chengwei Shao, Dehui Xiang:
Contrast Uncertainty Domain Alignment for Cross-Domain Pancreatic Image Segmentation. 1-5 - Natalia Valderrama, Ioannis Pitsiorlas, Luisa Vargas, Pablo Arbeláez, Maria A. Zuluaga:
Job-VS: Joint Brain-Vessel Segmentation in TOF-MRA Images. 1-5 - Yuki Shigeyasu, Kengo Araki, Shota Harada, Akihiko Yoshizawa, Kazuhiro Terada, Ryoma Bise:
Spatial Distribution-Based Pseudo Labeling for Pathological Image Segmentation. 1-5 - Ryan P. Cabeen, Joseph Mandeville, Fahmeed Hyder, Basavaraju G. Sanganahalli, Daniel R. Thedens, Ali S. Arbab, Shuning Huang, Adnan Bibic, Erendiz Tarakci, Jelena Mihailovic, Andreia Morais, Jessica Lamb, Karisma Nagarkatti, Arthur W. Toga, Patrick Lyden, Cenk Ayata:
Computational Image-Based Stroke Assessment for Evaluation of Cerebroprotectants with Longitudinal and Multi-Site Preclinical MRI. 1-5 - Yunjie Chen, Marius Staring, Jelmer M. Wolterink, Qian Tao:
Local Implicit Neural Representations for Multi-Sequence MRI Translation. 1-5 - Ivan Coronado, Samiksha Pachade, H. Dawoodally, Sergio Salazar Marioni, Juntao Yan, Rania Abdelkhaleq, M. Bahrainian, Amanda Jagolino-Cole, Roomasa Channa, Sunil A. Sheth, Luca Giancardo:
Foveal Avascular Zone Segmentation Using Deep Learning-Driven Image-Level Optimization and Fundus Photographs. 1-5 - Cheng Tang, Xinyi Zeng, Luping Zhou, Xi Wu, Jiliu Zhou, Peng Wang, Yan Wang:
Leveraging Hard Positives for Contrastive Learning in Semi-Supervised Medical Image Segmentation. 1-4 - Fuxin Fan, Yangkong Wang, Ludwig Ritschl, Ramyar Biniazan, Marcel Beister, Björn W. Kreher, Yixing Huang, Steffen Kappler, Andreas Maier:
Metal-conscious Embedding for CBCT Projection Inpainting. 1-5 - Zijian Chen, Soumya Das, Moo K. Chung:
Sulcal Pattern Matching with the Wasserstein Distance. 1-5 - Xirang Zhang, Yongyi Yang, P. Hendrik Pretorius, Michael A. King:
Assessment of Deep-Learning Based Motion Compensation on Detection of Perfusion Defects in Cardiac-Gated SPECT Images. 1-4 - Hao Xu, Tengfei Xue, Dongnan Liu, Fan Zhang, Carl-Fredrik Westin, Ron Kikinis, Lauren J. O'Donnell, Weidong Cai:
A Registration- and Uncertainty-Based Framework for White Matter Tract Segmentation with Only One Annotated Subject. 1-5 - Peng Jin, Yin-Ting Yeh, Jiarong Ye, Ziyang Wang, Yuan Xue, Na Zhang, Shengxi Huang, Elodie Ghedin, Huaguang Lu, Anthony Schmitt, Sharon X. Huang, Mauricio Terrones:
Strain-Level Identification and Analysis of Avian Coronavirus Using Raman Spectroscopy and Interpretable Machine Learning. 1-5 - Tuan D. Pham, Xiao-Feng Sun:
Wavelet Scattering of RhoB-Expressed Deep-Learning Features for Rectal Cancer Prognosis. 1-4 - Jiayang Zhong, Lawrence H. Staib, Rajesh Venkataraman, John A. Onofrey:
Integrating Prostate Specific Antigen Density Biomarker Into Deep Learning Prostate MRI Lesion Segmentation Models. 1-5 - Dónal M. McSweeney, Paul A. Bromiley, Andrew Green, Marcel van Herk, Alan McWilliam:
Fusion Contours as a Source of Segmentation Training Data: A Simulation Study. 1-6 - Aurélie Lebrun, Michel Bottlaender, Marie Sarazin, Yann Leprince:
Comparison between Synb0-Disco and Fieldmap-Based Methods to Correct for Distortion Artifacts in Diffusion MRI. 1-5 - Mahmood Haithami, Amr Ahmed, Iman Yi Liao, Hamid Abdullah Jalab:
Enhancing Polyp Segmentation Generalizability by Minimizing Images' Total Variation. 1-5 - Robail Yasrab, Mohammad Alsharid, Md. Mostafa Kamal Sarker, He Zhao, Aris T. Papageorghiou, J. Alison Noble:
Automated Description and Workflow Analysis of Fetal Echocardiography in First-Trimester Ultrasound Video Scans. 1-5 - Laifa Ma, Liangjun Chen, Fenqiang Zhao, Zhengwang Wu, Li Wang, Weili Lin, He Zhang, Kenli Li, Gang Li:
Geometric Constrained Deep Learning for Motion Correction of Fetal Brain Mr Images. 1-5 - Dalia Rodríguez-Salas, Mathias Öttl, Mathias Seuret, Kai Packhäuser, Andreas Maier:
Using Forestnets for Partial Fine-Tuning Prior to Breast Cancer Detection in Ultrasounds. 1-5 - Yikun Jiang, Xiaoru Yuan, Yuru Pei:
Spatially-Consistent Implicit Volumetric Function for Uni- and Bi-Planar X-Ray-Based Computed Tomography Reconstruction. 1-5 - Javier Bóbeda, Haizea Erostarbe, Maialen Stephens, Ángel Gaitán, Rahul Kumar, Jorge Nuche, Irene Marco, Juan Delgado, Jesús Ruiz-Cabello, Karen López-Linares:
Automatic Tool for Pulmonary Artery Hemodynamic Assessment from 4D flow MRI. 1-5 - Sze-Nung Leung, Jason A. Dowling, Jurgen Fripp, Kai-Kai Shen, Shekhar S. Chandra:
Medical Shape Pattern Analysis with MeshCNN. 1-5 - Fengjun Zhao, Yongfeng Chen, Kaiming Huang, Xiaowei He, Xin Chen, Yuqing Hou:
Semi-BGSegNet: A Semi-Supervised Boundary-Guided Breast Tumor Segmentation Network. 1-5 - Yue Yu, Xuan Kan, Hejie Cui, Ran Xu, Yujia Zheng, Xiangchen Song, Yanqiao Zhu, Kun Zhang, Razieh Nabi, Ying Guo, Chao Zhang, Carl Yang:
Deep Dag Learning of Effective Brain Connectivity for FMRI Analysis. 1-5 - Sheng Chen, Zihao Tang, Dongnan Liu, Ché Fornusek, Michael Barnett<