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ORCIDFAIMI/EPIMI@MICCAI 2024: Marrakesh, Morocco
- Esther Puyol-Antón
, Ghada Zamzmi, Aasa Feragen, Andrew P. King, Veronika Cheplygina, Melanie Ganz-Benjaminsen, Enzo Ferrante, Ben Glocker, Eike Petersen, John S. H. Baxter, Islem Rekik, Roy Eagleson:
Ethics and Fairness in Medical Imaging - Second International Workshop on Fairness of AI in Medical Imaging, FAIMI 2024, and Third International Workshop on Ethical and Philosophical Issues in Medical Imaging, EPIMI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6-10, 2024, Proceedings. Lecture Notes in Computer Science 15198, Springer 2025, ISBN 978-3-031-72786-3
FAIMI
- Vincent Olesen, Nina Weng, Aasa Feragen, Eike Petersen:
Slicing Through Bias: Explaining Performance Gaps in Medical Image Analysis Using Slice Discovery Methods. 3-13 - Ralf Raumanns, Gerard Schouten, Josien P. W. Pluim, Veronika Cheplygina:
Dataset Distribution Impacts Model Fairness: Single Vs. Multi-task Learning. 14-23 - Pritam Mukherjee, Ronald M. Summers:
AI Fairness in Medical Imaging: Controlling for Disease Severity. 24-33 - Philipp Kaess, Alexander Ziller, Lea Mantz, Daniel Rueckert, Florian J. Fintelmann, Georgios Kaissis:
Fair and Private CT Contrast Agent Detection. 34-45 - Vien Ngoc Dang, Adrià Casamitjana, Jerónimo Hernández-González, Karim Lekadir, Alzheimer's Disease Neuroimaging Initiative:
Mitigating Overdiagnosis Bias in CNN-Based Alzheimer's Disease Diagnosis for the Elderly. 46-55 - Samia Belhadj, Sanguk Park, Ambika Seth, Hesham Dar, Thijs Kooi:
Positive-Sum Fairness: Leveraging Demographic Attributes to Achieve Fair AI Outcomes Without Sacrificing Group Gains. 56-66 - Christopher Boland, Owen Anderson, Keith A. Goatman, John H. Hipwell, Sotirios A. Tsaftaris, Sonia Dahdouh:
All You Need Is a Guiding Hand: Mitigating Shortcut Bias in Deep Learning Models for Medical Imaging. 67-77 - John McCabe, Daryl Cheng, Amyn Bhamani, Monica Mullin, Tanya Patrick, Arjun Nair, Sam M. Janes, Carole H. Sudre, Joseph Jacob:
Exploring Fairness in State-of-the-Art Pulmonary Nodule Detection Algorithms. 78-87 - Kate Cevora, Ben Glocker, Wenjia Bai:
Quantifying the Impact of Population Shift Across Age and Sex for Abdominal Organ Segmentation. 88-97 - Yuyang Xue, Junyu Yan, Raman Dutt, Fasih Haider, Jingshuai Liu, Steven McDonagh, Sotirios A. Tsaftaris:
BMFT: Achieving Fairness via Bias-Based Weight Masking Fine-Tuning. 98-108 - Dilermando Queiroz, André Anjos, Lilian Berton:
Using Backbone Foundation Model for Evaluating Fairness in Chest Radiography Without Demographic Data. 109-118 - Raissa Souza, Emma A. M. Stanley, Richard Camicioli, Oury Monchi, Zahinoor Ismail, Matthias Wilms, Nils D. Forkert:
Do Sites Benefit Equally from Distributed Learning in Medical Image Analysis? 119-128 - Lakshika Rathi, Giacomo Nebbia, Ken Chang, Sourav Kumar, Aarushi Gupta, Syed Rakin Ahmed, Jay B. Patel, Christopher Clark, Yoga Advaith Veturi, Aaron S. Coyner, Aakanksha Rana, Christopher P. Bridge, Stephen McNamara, J. Peter Campbell, Matthew D. Li, Jayashree Kalpathy-Cramer, Praveer Singh:
Cycle-GANs Generated Difference Maps to Interpret Race Prediction from Medical Images. 129-139 - Anissa Alloula, Rima Mustafa, Daniel R. McGowan, Bartlomiej W. Papiez:
On Biases in a UK Biobank-Based Retinal Image Classification Model. 140-150 - Ricardo Coimbra Brioso, Damiano Dei, Nicola Lambri, Pietro Mancosu, Marta Scorsetti, Daniele Loiacono:
Investigating Gender Bias in Lymph-Node Segmentation with Anatomical Priors. 151-160
EPIMI
- Emma A. M. Stanley, Raissa Souza, Anthony J. Winder, Matthias Wilms, G. Bruce Pike, Gabrielle Dagasso, Christopher Nielsen, Sarah J. MacEachern, Nils D. Forkert:
Assessing the Impact of Sociotechnical Harms in AI-Based Medical Image Analysis. 163-175 - Debesh Jha, Ashish Rauniyar, Desta Haileselassie Hagos, Vanshali Sharma, Nikhil Kumar Tomar, Zheyuan Zhang, Ilkin Isler, Gorkem Durak, Michael B. Wallace, Cemal Yazici, Tyler M. Berzin, Koushik Biswas, Ulas Bagci:
Practical and Ethical Considerations for Generative AI in Medical Imaging. 176-187
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