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ORCID28th IPMI 2023: San Carlos de Bariloche, Argentina
- Alejandro F. Frangi
, Marleen de Bruijne, Demian Wassermann, Nassir Navab:
Information Processing in Medical Imaging - 28th International Conference, IPMI 2023, San Carlos de Bariloche, Argentina, June 18-23, 2023, Proceedings. Lecture Notes in Computer Science 13939, Springer 2023, ISBN 978-3-031-34047-5
Biomarkers
- Michele Guerreri, Sean C. Epstein, Hojjat Azadbakht, Hui Zhang:
Resolving Quantitative MRI Model Degeneracy with Machine Learning via Training Data Distribution Design. 3-14 - Alexandra L. Young, Leon M. Aksman, Daniel C. Alexander, Peter A. Wijeratne:
Subtype and Stage Inference with Timescales. 15-26
Brain Connectomics
- Huan Liu, Tingting Dan, Zhuobin Huang, Defu Yang, Won Hwa Kim, Minjeong Kim, Paul J. Laurienti, Guorong Wu:
HoloBrain: A Harmonic Holography for Self-organized Brain Function. 29-40 - Li Yang, Songyao Zhang, Weihan Zhang, Jingchao Zhou, Tianyang Zhong, Yaonai Wei, Xi Jiang, Tianming Liu, Junwei Han, Yixuan Yuan, Tuo Zhang:
Species-Shared and -Specific Brain Functional Connectomes Revealed by Shared-Unique Variational Autoencoder. 41-52 - Niharika Shimona D'Souza, Archana Venkataraman:
mSPD-NN: A Geometrically Aware Neural Framework for Biomarker Discovery from Functional Connectomics Manifolds. 53-65
Computer-Aided Diagnosis/Surgery
- Shizhan Gong, Cheng Chen, Yuqi Gong, Nga Yan Chan, Wenao Ma, Calvin Hoi-Kwan Mak, Jill M. Abrigo, Qi Dou:
Diffusion Model Based Semi-supervised Learning on Brain Hemorrhage Images for Efficient Midline Shift Quantification. 69-81 - Tom Nuno Wolf, Sebastian Pölsterl, Christian Wachinger:
Don't PANIC: Prototypical Additive Neural Network for Interpretable Classification of Alzheimer's Disease. 82-94 - Jiangchuan Du, Yuan Zhou:
Filtered Trajectory Recovery: A Continuous Extension to Event-Based Model for Alzheimer's Disease Progression Modeling. 95-106 - Gary Sarwin, Alessandro Carretta, Victor E. Staartjes, Matteo Zoli, Diego Mazzatenta, Luca Regli, Carlo Serra, Ender Konukoglu:
Live Image-Based Neurosurgical Guidance and Roadmap Generation Using Unsupervised Embedding. 107-118 - Bo Zhou, Yingda Xia, Jiawen Yao, Le Lu, Jingren Zhou, Chi Liu, James S. Duncan, Ling Zhang:
Meta-information-Aware Dual-path Transformer for Differential Diagnosis of Multi-type Pancreatic Lesions in Multi-phase CT. 119-131 - Lin Zhao, Hexin Dong, Ping Wu, Jiaying Lu, Le Lu, Jingren Zhou, Tianming Liu, Li Zhang, Ling Zhang, Yuxing Tang, Chuantao Zuo:
MetaViT: Metabolism-Aware Vision Transformer for Differential Diagnosis of Parkinsonism with 18F-FDG PET. 132-144 - Jianxin Liu, Rongjun Ge, Peng Wan, Qi Zhu, Daoqiang Zhang, Wei Shao:
Multi-task Multi-instance Learning for Jointly Diagnosis and Prognosis of Early-Stage Breast Invasive Carcinoma from Whole-Slide Pathological Images. 145-157 - Wenlong Deng, Yuan Zhong, Qi Dou, Xiaoxiao Li:
On Fairness of Medical Image Classification with Multiple Sensitive Attributes via Learning Orthogonal Representations. 158-169 - Ario Sadafi, Oleksandra Adonkina, Ashkan Khakzar, Peter Lienemann, Rudolf Matthias Hehr, Daniel Rueckert, Nassir Navab, Carsten Marr:
Pixel-Level Explanation of Multiple Instance Learning Models in Biomedical Single Cell Images. 170-182 - Noah Maul, Katharina Zinn, Fabian Wagner, Mareike Thies, Maximilian Rohleder, Laura Pfaff, Markus Kowarschik, Annette Birkhold, Andreas K. Maier:
Transient Hemodynamics Prediction Using an Efficient Octree-Based Deep Learning Model. 183-194 - Jiahong Ouyang, Li Chen, Gary Y. Li, Naveen Balaraju, Shubham Patil, Courosh Mehanian, Sourabh Kulhare, Rachel Millin, Kenton W. Gregory, Cynthia Gregory, Meihua Zhu, David O. Kessler, Laurie Malia, Almaz Dessie, Joni Rabiner, Di Coneybeare, Bo Shopsin, Andrew Hersh, Cristian Madar, Jeffrey Shupp, Laura S. Johnson, Jacob Avila, Kristin Dwyer, Peter Weimersheimer, Balasundar Raju, Jochen Kruecker, Alvin Chen:
Weakly Semi-supervised Detection in Lung Ultrasound Videos. 195-207 - Raghav Tandon, Anna Kirkpatrick, Cassie S. Mitchell:
sEBM: Scaling Event Based Models to Predict Disease Progression via Implicit Biomarker Selection and Clustering. 208-221
Domain Adaptation
- Ziqi Wen, Xinru Zhang, Chuyang Ye:
Source-Free Domain Adaptation for Medical Image Segmentation via Selectively Updated Mean Teacher. 225-236 - Jianghao Wu, Ran Gu, Tao Lu, Shaoting Zhang, Guotai Wang:
UPL-TTA: Uncertainty-Aware Pseudo Label Guided Fully Test Time Adaptation for Fetal Brain Segmentation. 237-249 - Jiexiang Wang, Chaoqi Chen:
Unsupervised Adaptation of Polyp Segmentation Models via Coarse-to-Fine Self-Supervision. 250-262
Geometric Deep Learning
- Tai Hasegawa, Helena Arvidsson, Nikolce Tudzarovski, Karl Meinke, Rachael V. Sugars, Aravind Ashok Nair:
Edge-Based Graph Neural Networks for Cell-Graph Modeling and Prediction. 265-277 - Jinghan Huang, Moo K. Chung, Anqi Qiu:
Heterogeneous Graph Convolutional Neural Network via Hodge-Laplacian for Brain Functional Data. 278-290 - Haocheng Dai, Martin Bauer, P. Thomas Fletcher, Sarang C. Joshi:
Modeling the Shape of the Brain Connectome via Deep Neural Networks. 291-302 - Mohammad Farazi, Zhangsihao Yang, Wenhui Zhu, Peijie Qiu, Yalin Wang:
TetCNN: Convolutional Neural Networks on Tetrahedral Meshes. 303-315
Groupwise Atlasing
- Xin Wang, Xinzhe Luo, Xiahai Zhuang:
BInGo: Bayesian Intrinsic Groupwise Registration via Explicit Hierarchical Disentanglement. 319-331 - Amin Nejatbakhsh, Neel Dey, Vivek Venkatachalam, Eviatar Yemini, Liam Paninski, Erdem Varol:
Learning Probabilistic Piecewise Rigid Atlases of Model Organisms via Generative Deep Networks. 332-343
Harmonization/Federated Learning
- Farzad Beizaee, Christian Desrosiers, Gregory A. Lodygensky, Jose Dolz:
Harmonizing Flows: Unsupervised MR Harmonization Based on Normalizing Flows. 347-359 - Yongsong Huang, Wanqing Xie, Mingzhen Li, Mingmei Cheng, Jinzhou Wu, Weixiao Wang, Jane You, Xiaofeng Liu:
Vicinal Feature Statistics Augmentation for Federated 3D Medical Volume Segmentation. 360-371
Image Synthesis
- Caiwen Jiang, Yongsheng Pan, Tianyu Wang, Qing Chen, Junwei Yang, Li Ding, Jiameng Liu, Zhongxiang Ding, Dinggang Shen:
S2DGAN: Generating Dual-energy CT from Single-energy CT for Real-time Determination of Intracerebral Hemorrhage. 375-387 - Jee Seok Yoon, Chenghao Zhang, Heung-Il Suk, Jia Guo, Xiaoxiao Li:
SADM: Sequence-Aware Diffusion Model for Longitudinal Medical Image Generation. 388-400
Image Enhancement
- Yikang Liu, Eric Z. Chen, Xiao Chen, Terrence Chen, Shanhui Sun:
An Unsupervised Framework for Joint MRI Super Resolution and Gibbs Artifact Removal. 403-414 - Wenhui Zhu, Peijie Qiu, Oana M. Dumitrascu, Jacob M. Sobczak, Mohammad Farazi, Zhangsihao Yang, Keshav Nandakumar, Yalin Wang:
OTRE: Where Optimal Transport Guided Unpaired Image-to-Image Translation Meets Regularization by Enhancing. 415-427 - Shijie Huang, Geng Chen, Kaicong Sun, Zhiming Cui, Xukun Zhang, Peng Xue, Xuan Zhang, He Zhang, Dinggang Shen:
Super-Resolution Reconstruction of Fetal Brain MRI with Prior Anatomical Knowledge. 428-441
Multimodal Learning
- Yunyi Liu, Zhanyu Wang, Dong Xu, Luping Zhou:
Q2ATransformer: Improving Medical VQA via an Answer Querying Decoder. 445-456 - Peiqi Wang, William M. Wells III, Seth J. Berkowitz, Steven Horng, Polina Golland:
Using Multiple Instance Learning to Build Multimodal Representations. 457-470 - Tom van Sonsbeek, Marcel Worring:
X-TRA: Improving Chest X-ray Tasks with Cross-Modal Retrieval Augmentation. 471-482
Optimization
- Sonia Martinot, Nikos Komodakis, Maria Vakalopoulou, Norbert Bus, Charlotte Robert, Eric Deutsch, Nikos Paragios:
Differentiable Gamma Index-Based Loss Functions: Accelerating Monte-Carlo Radiotherapy Dose Simulation. 485-496 - Abdalla Bani, Sung Min Ha, Pan Xiao, Thomas Earnest, John Lee, Aristeidis Sotiras:
Scalable Orthonormal Projective NMF via Diversified Stochastic Optimization. 497-508
Reconstruction
- Fergus Shone, Nishant Ravikumar, Toni Lassila, Michael MacRaild, Yongxing Wang, Zeike A. Taylor, Peter K. Jimack, Erica Dall' Armellina, Alejandro F. Frangi:
Deep Physics-Informed Super-Resolution of Cardiac 4D-Flow MRI. 511-522 - Bo Zhou, Yu-Jung Tsai, Jiazhen Zhang, Xueqi Guo, Huidong Xie, Xiongchao Chen, Tianshun Miao, Yihuan Lu, James S. Duncan, Chi Liu:
Fast-MC-PET: A Novel Deep Learning-Aided Motion Correction and Reconstruction Framework for Accelerated PET. 523-535 - Junjie Zhao, Siyuan Liu, Sahar Ahmad, Pew-Thian Yap:
MeshDeform: Surface Reconstruction of Subcortical Structures via Human Brain MRI. 536-547 - Wenqi Huang, Hongwei Bran Li, Jiazhen Pan, Gastão Cruz, Daniel Rueckert, Kerstin Hammernik:
Neural Implicit k-Space for Binning-Free Non-Cartesian Cardiac MR Imaging. 548-560
Registration
- Jose J. Bouza, Chun-Hao Yang, Baba C. Vemuri:
Geometric Deep Learning for Unsupervised Registration of Diffusion Magnetic Resonance Images. 563-575 - Jian Wang, Jiarui Xing, Jason Druzgal, William M. Wells III, Miaomiao Zhang:
MetaMorph: Learning Metamorphic Image Transformation with Appearance Changes. 576-587 - Nian Wu, Miaomiao Zhang:
NeurEPDiff: Neural Operators to Predict Geodesics in Deformation Spaces. 588-600 - Zhe Min, Zachary M. C. Baum, Shaheer U. Saeed, Mark Emberton, Dean C. Barratt, Zeike A. Taylor, Yipeng Hu:
Non-rigid Medical Image Registration using Physics-informed Neural Networks. 601-613 - Antoine Legouhy, Ross Callaghan, Hojjat Azadbakht, Hui Zhang:
POLAFFINI: Efficient Feature-Based Polyaffine Initialization for Improved Non-linear Image Registration. 614-625
Segmentation
- Wan Liu, Chuyang Ye:
Better Generalization of White Matter Tract Segmentation to Arbitrary Datasets with Scaled Residual Bootstrap. 629-640 - Chenyu You, Weicheng Dai, Yifei Min, Lawrence H. Staib, James S. Duncan:
Bootstrapping Semi-supervised Medical Image Segmentation with Anatomical-Aware Contrastive Distillation. 641-653 - Manxi Lin, Kilian Zepf, Anders Nymark Christensen, Zahra Bashir, Morten Bo Søndergaard Svendsen, Martin Grønnebæk Tolsgaard, Aasa Feragen:
DTU-Net: Learning Topological Similarity for Curvilinear Structure Segmentation. 654-666 - Anne-Marie Rickmann, Murong Xu, Tom Nuno Wolf, Oksana P. Kovalenko, Christian Wachinger:
HALOS: Hallucination-Free Organ Segmentation After Organ Resection Surgery. 667-678 - Wentao Pan, Jiangpeng Yan, Hanbo Chen, Jiawei Yang, Zhe Xu, Xiu Li, Jianhua Yao:
Human-Machine Interactive Tissue Prototype Learning for Label-Efficient Histopathology Image Segmentation. 679-691 - Sadhana Ravikumar, Ranjit Ittyerah, Sydney Lim, Long Xie, Sandhitsu R. Das, Pulkit Khandelwal, Laura E. M. Wisse, Madigan L. Bedard, John L. Robinson, Terry Schuck, Murray Grossman, John Q. Trojanowski, Edward B. Lee, M. Dylan Tisdall, Karthik Prabhakaran, John A. Detre, David J. Irwin, Winifred Trotman, Gabor Mizsei, Emilio Artacho-Pérula, Maria Mercedes Iñiguez de Onzoño Martin, María del Mar Arroyo Jiménez, Mónica Muñoz López, Francisco Javier Molina Romero, Maria del Pilar Marcos Rabal, Sandra Cebada Sánchez, José Carlos Delgado González, Carlos de la Rosa Prieto, Marta Córcoles Parada, David A. Wolk, Ricardo Insausti, Paul A. Yushkevich:
Improved Segmentation of Deep Sulci in Cortical Gray Matter Using a Deep Learning Framework Incorporating Laplace's Equation. 692-704 - John Kalkhof, Camila González, Anirban Mukhopadhyay:
Med-NCA: Robust and Lightweight Segmentation with Neural Cellular Automata. 705-716 - Bach Ngoc Kim, Jose Dolz, Pierre-Marc Jodoin, Christian Desrosiers:
Mixup-Privacy: A Simple yet Effective Approach for Privacy-Preserving Segmentation. 717-729 - Yi Lin, Dong Zhang, Xiao Fang, Yufan Chen, Kwang-Ting Cheng, Hao Chen:
Rethinking Boundary Detection in Deep Learning Models for Medical Image Segmentation. 730-742 - Lei Zhou, Huidong Liu, Joseph Bae, Junjun He, Dimitris Samaras, Prateek Prasanna:
Token Sparsification for Faster Medical Image Segmentation. 743-754 - Florian Kofler, Suprosanna Shit, Ivan Ezhov, Lucas Fidon, Izabela Horvath, Rami Al-Maskari, Hongwei Bran Li, Harsharan Bhatia, Timo Loehr, Marie Piraud, Ali Ertürk, Jan Kirschke, Jan C. Peeken, Tom Vercauteren, Claus Zimmer, Benedikt Wiestler, Bjoern H. Menze:
blob loss: Instance Imbalance Aware Loss Functions for Semantic Segmentation. 755-767
Self Supervised Learning
- Fabian Wagner, Mareike Thies, Laura Pfaff, Noah Maul, Sabrina Pechmann, Mingxuan Gu, Jonas Utz, Oliver Aust, Daniela Weidner, Georgiana Neag, Stefan Uderhardt, Jang Hwan Choi, Andreas Maier:
Noise2Contrast: Multi-contrast Fusion Enables Self-supervised Tomographic Image Denoising. 771-782 - Jingwei Zhang, Saarthak Kapse, Ke Ma, Prateek Prasanna, Maria Vakalopoulou, Joel H. Saltz, Dimitris Samaras:
Precise Location Matching Improves Dense Contrastive Learning in Digital Pathology. 783-794
Surface Analysis and Segmentation
- Shuxian Wang, Yubo Zhang, Sarah K. McGill, Julian G. Rosenman, Jan-Michael Frahm, Soumyadip Sengupta, Stephen M. Pizer:
A Surface-Normal Based Neural Framework for Colonoscopy Reconstruction. 797-809 - Ye Han, Jared Vicory, Guido Gerig, Patricia Sabin, Hannah Dewey, Silvani Amin, Ana Sulentic, Christian Herz, Matthew A. Jolley, Beatriz Paniagua, James Fishbaugh:
Hierarchical Geodesic Polynomial Model for Multilevel Analysis of Longitudinal Shape. 810-821 - Xiaodong Wu, Leixin Zhou, Fahim A. Zaman, Bensheng Qiu, John M. Buatti:
Model-Informed Deep Learning for Surface Segmentation in Medical Imaging. 822-834
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