Abstract is missing.
- Reducing Manual Annotation Costs for Cell Segmentation by Upgrading Low-Quality AnnotationsSerban Vadineanu, Daniël Maria Pelt, Oleh Dzyubachyk, Kees Joost Batenburg. 3-13 [doi]
- ScribSD: Scribble-Supervised Fetal MRI Segmentation Based on Simultaneous Feature and Prediction Self-distillationYijie Qu, Qianfei Zhao, Linda Wei, Tao Lu, Shaoting Zhang 0001, Guotai Wang. 14-23 [doi]
- Label-Efficient Contrastive Learning-Based Model for Nuclei Detection and Classification in 3D Cardiovascular Immunofluorescent ImagesNazanin Moradinasab, Rebecca A. Deaton, Laura S. Shankman, Gary K. Owens, Donald E. Brown. 24-34 [doi]
- Affordable Graph Neural Network Framework Using Topological Graph ContractionChristopher Adnel, Islem Rekik. 35-46 [doi]
- Dual-Domain Iterative Network with Adaptive Data Consistency for Joint Denoising and Few-Angle Reconstruction of Low-Dose Cardiac SPECTXiongchao Chen, Bo Zhou 0009, Huidong Xie, Xueqi Guo, Qiong Liu, Albert J. Sinusas, Chi Liu. 49-59 [doi]
- A Multitask Framework for Label Refinement and Lesion Segmentation in Clinical Brain ImagingYang Yu, Jiahao Wang, Ashish Jith Sreejith Kumar, Bryan Tan, Navya Vanjavaka, Nurul Hafidzah Rahim, Alistair Koh, Shaheen Low, Yih Yian Sitoh, Hanry Yu, Pavitra Krishnaswamy, Ivan Ho Mien. 60-70 [doi]
- COVID-19 Lesion Segmentation Framework for the Contrast-Enhanced CT in the Absence of Contrast-Enhanced CT AnnotationsMaryna Kvasnytsia, Abel Díaz Berenguer, Hichem Sahli, Jef Vandemeulebroucke. 71-81 [doi]
- Feasibility of Universal Anomaly Detection Without Knowing the Abnormality in Medical ImagesCan Cui, Yaohong Wang, Shunxing Bao, Yucheng Tang, Ruining Deng, Lucas W. Remedios, Zuhayr Asad, Joseph T. Roland, Ken S. Lau, Qi Liu 0024, Lori A. Coburn, Keith T. Wilson, Bennett A. Landman, Yuankai Huo. 82-92 [doi]
- Decoupled Conditional Contrastive Learning with Variable Metadata for Prostate Lesion DetectionCamille Ruppli, Pietro Gori, Roberto Ardon, Isabelle Bloch. 95-105 [doi]
- FBA-Net: Foreground and Background Aware Contrastive Learning for Semi-Supervised Atrium SegmentationYunsung Chung, Chanho Lim, Chao Huang, Nassir Marrouche, Jihun Hamm. 106-116 [doi]
- Masked Image Modeling for Label-Efficient Segmentation in Two-Photon Excitation MicroscopyTony Xu, Matthew Rozak, Emmanuel E. Ntiri, Adrienne Dorr, James R. Mester, Bojana Stefanovic, Anne L. Martel, Maged Goubran. 117-127 [doi]
- Automatic Quantification of COVID-19 Pulmonary Edema by Self-supervised Contrastive LearningZhaohui Liang, Zhiyun Xue, Sivaramakrishnan Rajaraman, Yang Feng, Sameer K. Antani. 128-137 [doi]
- SDLFormer: A Sparse and Dense Locality-Enhanced Transformer for Accelerated MR Image ReconstructionRahul G. S., Sriprabha Ramanarayanan, Mohammad Al Fahim, Keerthi Ram, Preejith S. P, Mohanasankar Sivaprakasam. 138-147 [doi]
- Robust Unsupervised Image to Template Registration Without Image Similarity LossSlim Hachicha, Célia Le, Valentine Wargnier-Dauchelle, Michaël Sdika. 148-157 [doi]
- A Dual-Branch Network with Mixed and Self-Supervision for Medical Image Segmentation: An Application to Segment Edematous Adipose TissueJianfei Liu, Omid Shafaat, Ronald M. Summers. 158-167 [doi]
- Combining Weakly Supervised Segmentation with Multitask Learning for Improved 3D MRI Brain Tumour ClassificationSajith Rajapaksa, Khashayar Namdar, Farzad Khalvati. 171-180 [doi]
- Exigent Examiner and Mean Teacher: An Advanced 3D CNN-Based Semi-Supervised Brain Tumor Segmentation FrameworkZiyang Wang, Irina Voiculescu. 181-190 [doi]
- Extremely Weakly-Supervised Blood Vessel Segmentation with Physiologically Based Synthesis and Domain AdaptationPeidi Xu, Blaire Lee, Olga V. Sosnovtseva, Charlotte Mehlin Sørensen, Kenny Erleben, Sune Darkner. 191-201 [doi]
- Multi-task Learning for Few-Shot Differential Diagnosis of Breast Cancer Histopathology ImagesKrishna Thoriya, Preeti Mutreja, Sumit Kalra, Angshuman Paul. 202-210 [doi]
- Test-Time Augmentation-Based Active Learning and Self-training for Label-Efficient SegmentationBella Specktor-Fadida, Anna Levchakov, Dana Schonberger, Liat Ben-Sira, Dafna Ben-Bashat, Leo Joskowicz. 213-223 [doi]
- Active Transfer Learning for 3D Hippocampus SegmentationJi Wu, Zhongfeng Kang, Sebastian Nørgaard Llambias, Mostafa Mehdipour-Ghazi, Mads Nielsen. 224-234 [doi]
- Using Training Samples as Transitive Information Bridges in Predicted 4D MRIGino Gulamhussene, Oleksii Bashkanov, Jazan Omari, Maciej Pech, Christian Hansen 0001, Marko Rak. 237-245 [doi]
- To Pretrain or Not to Pretrain? A Case Study of Domain-Specific Pretraining for Semantic Segmentation in HistopathologyTushar Kataria, Beatrice Knudsen, Shireen Y. Elhabian. 246-256 [doi]
- Large-Scale Pretraining on Pathological Images for Fine-Tuning of Small Pathological BenchmarksMasakata Kawai, Noriaki Ota, Shinsuke Yamaoka. 257-267 [doi]