default search action
DEMI@MICCAI 2024: Marrakesh, Morocco
- Binod Bhattarai, Sharib Ali, Anita Rau, Razvan Caramalau, Anh Nguyen, Prashnna Gyawali, Ana I. L. Namburete, Danail Stoyanov:
Data Engineering in Medical Imaging - Second MICCAI Workshop, DEMI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings. Lecture Notes in Computer Science 15265, Springer 2025, ISBN 978-3-031-73747-3 - Halid Ziya Yerebakan, Yoshihisa Shinagawa, Gerardo Hermosillo Valadez:
Real Time Multi Organ Classification on Computed Tomography Images. 1-10 - George Batchkala, Bin Li, Jens Rittscher:
Evaluating Histopathology Foundation Models for Few-Shot Tissue Clustering: An Application to LC25000 Augmented Dataset Cleaning. 11-21 - Mélanie Roschewitz, Fabio De Sousa Ribeiro, Tian Xia, Galvin Khara, Ben Glocker:
Counterfactual Contrastive Learning: Robust Representations via Causal Image Synthesis. 22-32 - Sandesh Pokhrel, Sanjay Bhandari, Eduard Vazquez, Tryphon Lambrou, Prashnna K. Gyawali, Binod Bhattarai:
TTA-OOD: Test-Time Augmentation for Improving Out-of-Distribution Detection in Gastrointestinal Vision. 33-42 - Tim J. M. Jaspers, Ronald L. P. D. de Jong, Yasmina Al Khalil, Tijn Zeelenberg, Carolus H. J. Kusters, Yiping Li, Romy C. van Jaarsveld, Franciscus H. A. Bakker, Jelle P. Ruurda, Willem M. Brinkman, Peter H. N. de With, Fons van der Sommen:
Exploring the Effect of Dataset Diversity in Self-supervised Learning for Surgical Computer Vision. 43-53 - Jiamu Wang, JinTae Kwak:
USegMix: Unsupervised Segment Mix for Efficient Data Augmentation in Pathology Images. 54-63 - Krishan Agyakari Raja Babu, Rachana Sathish, Mrunal Pattanaik, Rahul Venkataramani:
Synthetic Simplicity: Unveiling Bias in Medical Data Augmentation. 64-72 - Benjamin Jin, Maria del C. Valdés Hernández, Alessandro Fontanella, Wenwen Li, Eleanor Platt, Paul A. Armitage, Amos J. Storkey, Joanna M. Wardlaw, Grant Mair:
Pre-processing and Quality Control of Large Clinical CT Head Datasets for Intracranial Arterial Calcification Segmentation. 73-83 - Iván Reyes-Amezcua, Ricardo Espinosa, Christian Daul, Gilberto Ochoa-Ruiz, Andres Mendez-Vazquez:
EndoDepth: A Benchmark for Assessing Robustness in Endoscopic Depth Prediction. 84-94 - Jingxuan Kang, Tudor Jianu, Baoru Huang, Binod Bhattarai, Ngan Le, Frans Coenen, Anh Nguyen:
Translating Simulation Images to X-Ray Images via Multi-scale Semantic Matching. 95-104 - Abder-Rahman Ali, Anthony E. Samir:
Simple is More: Efficient Liver View Classification in Ultrasound Images Using Minimal Labeled Data and Simple Neural Network Architecture. 105-114 - Rob A. J. de Mooij, Josien P. W. Pluim, Cian M. Scannell:
Self-Supervised Pretraining for Cardiovascular Magnetic Resonance Cine Segmentation. 115-124 - Hyeonmin Kim, Chanyang Seo, Yunnie Cho, Tae Keun Yoo:
Patient-Level Contrastive Learning for Enhanced Biomarker Prediction in Retinal Imaging. 125-133 - Jacob Thrasher, Annahita Amireskandari, Prashnna K. Gyawali:
Enhancing Retinal Disease Classification from OCTA Images via Active Learning Techniques. 134-143 - Pedro Esteban Chavarrias-Solano, Binod Bhattarai, Sharib Ali:
Improving NeRF Representation with No Pose Prior for Novel View Synthesis in Colonoscopy. 144-154 - Pranav Poudel, Shrawan Kumar Thapa, Sudarshan Regmi, Binod Bhattarai, Danail Stoyanov:
Task-Aware Active Learning for Endoscopic Polyp Segmentation. 155-165 - Sandesh Pokhrel, Sanjay Bhandari, Eduard Vazquez, Yash Raj Shrestha, Binod Bhattarai:
Cross-Task Data Augmentation by Pseudo-Label Generation for Region Based Coronary Artery Instance Segmentation. 166-175 - Lei He, Zhaohui Liu, Qiude Zhang, Liang Zhou, Yuxin Cai, Jing Yuan, Mingyue Ding, Ming Yuchi, Wu Qiu:
Optimizing Delay Estimation in Breast RUCT Reconstruction Using Self-supervised Blind Segment Network. 176-185
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.