TY - GEN
T1 - PMIL
T2 - 2025 IEEE International Symposium on Circuits and Systems, ISCAS 2025
AU - Obeid, Ahmad
AU - Sohail, Anabia
AU - Boumaraf, Said
AU - Liu, Xiabi
AU - Javed, Sajid
AU - Almarzouqi, Hasan
AU - Dias, Jorge
AU - Bennamoun, Mohammed
AU - Werghi, Naoufel
AU - Elfadel, Ibrahim
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Deep learning models have achieved remarkable success in pathology image analysis. However, they still face challenges in effectively modeling fine-grained, object-level features. Topological Data Analysis (TDA) has shown promise for addressing these issues but remains underexplored, particularly for whole-slide pathology applications. Additionally, the effectiveness of TDA has yet to be firmly established, as current studies largely use small-scale datasets. In this work, we address these gaps by introducing Persistent Homology in Multiple Instance Learning (PMIL), the first adaptable TDA-based module within the MIL framework. We validate our approach on a large-scale classification dataset, benchmarking against multiple state-of-the-art methods.
AB - Deep learning models have achieved remarkable success in pathology image analysis. However, they still face challenges in effectively modeling fine-grained, object-level features. Topological Data Analysis (TDA) has shown promise for addressing these issues but remains underexplored, particularly for whole-slide pathology applications. Additionally, the effectiveness of TDA has yet to be firmly established, as current studies largely use small-scale datasets. In this work, we address these gaps by introducing Persistent Homology in Multiple Instance Learning (PMIL), the first adaptable TDA-based module within the MIL framework. We validate our approach on a large-scale classification dataset, benchmarking against multiple state-of-the-art methods.
KW - Histopathology
KW - Multiple Instance Learning
KW - Persistence Homology
KW - Topological Data Analysis
UR - https://www.scopus.com/pages/publications/105010635727
U2 - 10.1109/ISCAS56072.2025.11043738
DO - 10.1109/ISCAS56072.2025.11043738
M3 - Conference contribution
AN - SCOPUS:105010635727
T3 - Proceedings - IEEE International Symposium on Circuits and Systems
BT - ISCAS 2025 - IEEE International Symposium on Circuits and Systems, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 25 May 2025 through 28 May 2025
ER -