1. Kumar Abhishek, Aditi Jain, and Ghassan Hamarneh. Investigating the Quality of DermaMNIST and Fitzpatrick17k Dermatological Image Datasets. Nature - Scientific Data, 12(196):1-21, 2025. Keyword(s): Dermatology/Skin, Machine Learning, Deep Learning, Software and Tools, Datasets, Annotation Noise and Disagreement. [bibtex-key = nature_sd2025]

1. Kumar Abhishek, Jeremy Kawahara, and Ghassan Hamarneh. What Can We Learn from Inter-Annotator Variability in Skin Lesion Segmentation?. In Medical Image Computing and Computer-Assisted Intervention (MICCAI) ISIC Skin Image Analysis Workshop (MICCAI ISIC), pages 000-000, 2025. Keyword(s): Dermatology/Skin, Color/Multichannel/Vector-valued, Machine Learning, Deep Learning, Segmentation, Annotation Noise and Disagreement. [bibtex-key = miccai_isic2025]



2. Kumar Abhishek, Jeremy Kawahara, and Ghassan Hamarneh. Segmentation Style Discovery: Application to Skin Lesion Images. In Medical Image Computing and Computer-Assisted Intervention (MICCAI) ISIC Skin Image Analysis Workshop (MICCAI ISIC), pages 24-34, 2024. Keyword(s): Dermatology/Skin, Color/Multichannel/Vector-valued, Machine Learning, Deep Learning, Segmentation, Annotation Noise and Disagreement. [bibtex-key = miccai_isic2024a]



3. Zahra Mirikharaji, Kumar Abhishek, Saeed Izadi, and Ghassan Hamarneh. D-LEMA: Deep Learning Ensembles from Multiple Annotations. In Biomedical Imaging and Artificial Intelligence (BMIAI) cluster Fall Research Showcase, Vancouver, Canada, pages 1, 2021. Keyword(s): Dermatology/Skin, Color/Multichannel/Vector-valued, Machine Learning, Deep Learning, Segmentation, Annotation Noise and Disagreement. [bibtex-key = bmiai2021b]



4. Zahra Mirikharaji, Yiqi Yan, and Ghassan Hamarneh. Learning to Segment Skin Lesions from Noisy Annotations. In Medical Image Computing and Computer-Assisted Intervention Workshop on Medical Image Learning with Less Labels and Imperfect Data (MICCAI MIL3ID), volume 11795, pages 207-215, 2019. Keyword(s): Machine Learning, Deep Learning, Segmentation, Dermatology/Skin, Annotation Noise and Disagreement. [bibtex-key = miccai_mil3id2019]

1. Zahra Mirikharaji, Kumar Abhishek, Saeed Izadi, and Ghassan Hamarneh. D-LEMA: Deep Learning Ensembles from Multiple Annotations - Application to Skin Lesion Segmentation. Technical report arXiv:2012.07206, 12 2020. Keyword(s): Dermatology/Skin, Machine Learning, Deep Learning, Segmentation, Annotation Noise and Disagreement. [bibtex-key = arxiv:2012.07206]



2. Zahra Mirikharaji, Yiqi Yan, and Ghassan Hamarneh. Learning to Segment Skin Lesions from Noisy Annotations. Technical report arxiv:1906.03815, 6 2019. Keyword(s): Machine Learning, Deep Learning, Segmentation, Annotation Noise and Disagreement. [bibtex-key = arxiv:1906.03815]

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All person copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

This document was translated from BibT_EX by bibtex2html