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ORCID12th CLIP/FAIMI/EPIMI@MICCAI 2023: Vancouver, BC, Canada
- Stefan Wesarg
, Esther Puyol-Antón, John S. H. Baxter, Marius Erdt, Klaus Drechsler, Cristina Oyarzun Laura, Moti Freiman, Yufei Chen, Islem Rekik, Roy Eagleson, Aasa Feragen, Andrew P. King, Veronika Cheplygina, Melanie Ganz-Benjaminsen, Enzo Ferrante, Ben Glocker, Daniel Moyer, Eike Petersen:
Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging - 12th International Workshop, CLIP 2023 1st International Workshop, FAIMI 2023 and 2nd International Workshop, EPIMI 2023 Vancouver, BC, Canada, October 8 and October 12, 2023 Proceedings. Lecture Notes in Computer Science 14242, Springer 2023, ISBN 978-3-031-45248-2
CLIP
- Lukas Zerweck, Stefan Wesarg, Jörn Kohlhammer, Michaela Köhm:
Automated Hand Joint Classification of Psoriatic Arthritis Patients Using Routinely Acquired Near Infrared Fluorescence Optical Imaging. 3-11 - Oded Schlesinger, Raj Kundu, Stefan M. Goetz, Guillermo Sapiro, Angel V. Peterchev, J. Matías Di Martino:
Automatic Neurocranial Landmarks Detection from Visible Facial Landmarks Leveraging 3D Head Priors. 12-20 - Jeffry Hartanto, Wee Kheng Leow, Andy Khye Soon Yew, Joyce Suang Bee Koh, Tet Sen Howe:
Subject-Specific Modelling of Knee Joint Motion for Routine Pre-operative Planning. 21-31 - Yael Tudela, Ana García-Rodríguez, Gloria Fernández-Esparrach, Jorge Bernal:
Towards Fine-Grained Polyp Segmentation and Classification. 32-42 - Luc Anchling, Nathan Hutin, Yanjie Huang, Selene Barone, Sophie Roberts, Felicia Miranda, Marcela Gurgel, Najla Al Turkestani, Sara Tinawi, Jonas Bianchi, Marilia Yatabe, Antonio C. Ruellas, Juan Carlos Prieto, Lucia H. S. Cevidanes:
Automated Orientation and Registration of Cone-Beam Computed Tomography Scans. 43-58 - Nitzan Avidan, Moti Freiman:
Deep Learning-Based Fast MRI Reconstruction: Improving Generalization for Clinical Translation. 59-69 - Gayeon Kim, Yufei Chen, Shuai Qi, Yujie Fu, Qi Zhang:
Uncertainty Based Border-Aware Segmentation Network for Deep Caries. 70-80 - Guy Shani, Moti Freiman, Yosef E. Maruvka:
An Efficient and Accurate Neural Network Tool for Finding Correlation Between Gene Expression and Histological Images. 81-88
FAIMI
- Chenwei Wu, Xiyu Yang, Emil Ghitman Gilkes, Hanwen Cui, Jiheon Choi, Na Sun, Ziqian Liao, Bo Fan, Mauricio Santillana, Leo A. Celi, Paolo Silva, Luis Filipe Nakayama:
De-identification and Obfuscation of Gender Attributes from Retinal Scans. 91-101 - Yuning Du, Yuyang Xue, Rohan Dharmakumar, Sotirios A. Tsaftaris:
Unveiling Fairness Biases in Deep Learning-Based Brain MRI Reconstruction. 102-111 - Sophie A. Martin, Francesca Biondo, James H. Cole, Beatrice Taylor:
Brain Matters: Exploring Bias in AI for Neuroimaging Research. 112-121 - Cosmin I. Bercea, Esther Puyol-Antón, Benedikt Wiestler, Daniel Rueckert, Julia A. Schnabel, Andrew P. King:
Bias in Unsupervised Anomaly Detection in Brain MRI. 122-131 - María Agustina Ricci Lara, Candelaria Mosquera, Enzo Ferrante, Rodrigo Echeveste:
Towards Unraveling Calibration Biases in Medical Image Analysis. 132-141 - Nina Weng, Siavash Arjomand Bigdeli, Eike Petersen, Aasa Feragen:
Are Sex-Based Physiological Differences the Cause of Gender Bias for Chest X-Ray Diagnosis? 142-152 - Rebecca S. Stone, Pedro Esteban Chavarrias-Solano, Andrew J. Bulpitt, David C. Hogg, Sharib Ali:
Bayesian Uncertainty-Weighted Loss for Improved Generalisability on Polyp Segmentation Task. 153-162 - Yun-Yang Huang, Venesia Chiuwanara, Chao-Hsuan Lin, Po-Chih Kuo:
Mitigating Bias in MRI-Based Alzheimer's Disease Classifiers Through Pruning of Deep Neural Networks. 163-171 - Vien Ngoc Dang, Adrià Casamitjana, Martijn P. A. Starmans, Carlos Martín-Isla, Jerónimo Hernández-González, Karim Lekadir, Alzheimer's Disease Neuroimaging Initiative:
Auditing Unfair Biases in CNN-Based Diagnosis of Alzheimer's Disease. 172-182 - Nilesh Kumar, Ruby Shrestha, Zhiyuan Li, Linwei Wang:
Distributionally Robust Optimization and Invariant Representation Learning for Addressing Subgroup Underrepresentation: Mechanisms and Limitations. 183-193 - Carolina Piçarra, Ben Glocker:
Analysing Race and Sex Bias in Brain Age Prediction. 194-204 - Mahsa Dibaji, Neha Gianchandani, Akhil Nair, Mansi Singhal, Roberto Souza, Mariana P. Bento:
Studying the Effects of Sex-Related Differences on Brain Age Prediction Using Brain MR Imaging. 205-214 - Tiarna Lee, Esther Puyol-Antón, Bram Ruijsink, Keana Aitcheson, Miaojing Shi, Andrew P. King:
An Investigation into the Impact of Deep Learning Model Choice on Sex and Race Bias in Cardiac MR Segmentation. 215-224 - Mohamed Huti, Tiarna Lee, Elinor Sawyer, Andrew P. King:
An Investigation into Race Bias in Random Forest Models Based on Breast DCE-MRI Derived Radiomics Features. 225-234 - Dewinda Julianensi Rumala:
How You Split Matters: Data Leakage and Subject Characteristics Studies in Longitudinal Brain MRI Analysis. 235-245 - Thorsten Kalb, Kaisar Kushibar, Celia Cintas, Karim Lekadir, Oliver Díaz, Richard Osuala:
Revisiting Skin Tone Fairness in Dermatological Lesion Classification. 246-255 - Ario Sadafi, Matthias Hehr, Nassir Navab, Carsten Marr:
A Study of Age and Sex Bias in Multiple Instance Learning Based Classification of Acute Myeloid Leukemia Subtypes. 256-265 - Nicolás Gaggion, Rodrigo Echeveste, Lucas Mansilla, Diego H. Milone, Enzo Ferrante:
Unsupervised Bias Discovery in Medical Image Segmentation. 266-275 - Amar Kumar, Nima Fathi, Raghav Mehta, Brennan Nichyporuk, Jean-Pierre R. Falet, Sotirios A. Tsaftaris, Tal Arbel:
Debiasing Counterfactuals in the Presence of Spurious Correlations. 276-286
EPIMI
- Raissa Souza, Emma A. M. Stanley, Nils D. Forkert:
On the Relationship Between Open Science in Artificial Intelligence for Medical Imaging and Global Health Equity. 289-300 - Matthew Rosenblatt, Javid Dadashkarimi, Dustin Scheinost:
Gradient-Based Enhancement Attacks in Biomedical Machine Learning. 301-312
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