2024-11-17-spyretos24a.md

title	booktitle	abstract	layout	series	publisher	issn	id	month	tex_title	firstpage	lastpage	page	order	cycles	bibtex_author	author	date	address	container-title	volume	genre	issued	pdf	extras
Early Fusion of H&E and IHC Histology Images for Pediatric Brain Tumor Classification	Proceedings of the MICCAI Workshop on Computational Pathology	This study explores the application of computational pathology to analyze pediatric brain tumors utilizing hematoxylin and eosin (H&E) and immunohistochemistry (IHC) whole slide images (WSIs). Experiments were conducted on H&E images for predicting tumor diagnosis and fusing them with unregistered IHC images to investigate potential improvements. Patch features were extracted using UNI, a vision transformer (ViT) model trained on H&E data, and whole slide classification was achieved using the attention-based multiple instance learning CLAM framework. In the astrocytoma tumor classification, early fusion of the H&E and IHC significantly improved the differentiation between tumor grades (balanced accuracy: 0.82 ± 0.05 vs 0.84 ± 0.05). In the multiclass classification, H&E images alone had a balanced accuracy of 0.79 ± 0.03 without any improvement obtained when fused with IHC. The findings highlight the potential of using multi-stain fusion to advance the diagnosis of pediatric brain tumors, however, further fusion methods should be investigated.	inproceedings	Proceedings of Machine Learning Research	PMLR	2640-3498	spyretos24a	0	Early Fusion of H&E and IHC Histology Images for Pediatric Brain Tumor Classification	192	202	192-202	192	false	Spyretos, Christoforos and Tampu, Iulian Emil and Khalili, Nadieh and Ladino, Juan Manuel Pardo and Nyman, Per and Blystad, Ida and Eklund, Anders and Haj-Hosseini, Neda	given family Christoforos Spyretos given family Iulian Emil Tampu given family Nadieh Khalili given family Juan Manuel Pardo Ladino given family Per Nyman given family Ida Blystad given family Anders Eklund given family Neda Haj-Hosseini	2024-11-17		Proceedings of the MICCAI Workshop on Computational Pathology	254	inproceedings	date-parts 2024 11 17	https://raw.githubusercontent.com/mlresearch/v254/main/assets/spyretos24a/spyretos24a.pdf