2024-12-23-shi24a.md

title	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
ThickV-Stain: Unprocessed Thick Tissues Virtual Staining for Rapid Intraoperative Histology	Virtual staining has shown great promise in realizing a rapid and low-cost clinical alternative for pathological examinations, eliminating the need for chemical reagents and laborious staining procedures. However, most of the previous studies mainly focus on thin slice samples, which still require tissue sectioning and are unsuitable for intraoperative use. In this paper, we propose a multi-scale model to virtually stain label-free and slide-free biological tissues, allowing hematoxylin- and eosin- (H&E) staining generation in less than a minute for an image with 100 million pixels. We name this ThickV-Stain model, specifically developed to virtually stain intricated and unprocessed thick tissues. We harness the ability of a multi-scale network to encourage the model to capture multiple-level micromorphological characteristics from low-resolution images. Experimental results highlight the advantages of our multi-scale method for virtual staining on unprocessed thick samples. We also show the effectiveness of ThickV-Stain on thin sections, showing generalizability to other clinical workflows. The proposed method enables us to obtain virtually stained images from unstained samples within minutes and can be seamlessly integrated with downstream pathological analysis tasks, providing an efficient alternative scheme for intraoperative assessment as well as general pathological examination.	inproceedings	Proceedings of Machine Learning Research	PMLR	2640-3498	shi24a	0	ThickV-Stain: Unprocessed Thick Tissues Virtual Staining for Rapid Intraoperative Histology	1434	1447	1434-1447	1434	false	Shi, Lulin and Hou, Xingzhong and Wong, Ivy H. M. and Chan, Simon C. K. and Chen, Zhenghui and Lo, Claudia T. K. and Wong, Terence T. W.	given family Lulin Shi given family Xingzhong Hou given family Ivy H. M. Wong given family Simon C. K. Chan given family Zhenghui Chen given family Claudia T. K. Lo given family Terence T. W. Wong	2024-12-23		Proceedings of The 7nd International Conference on Medical Imaging with Deep Learning	250	inproceedings	date-parts 2024 12 23	https://raw.githubusercontent.com/mlresearch/v250/main/assets/shi24a/shi24a.pdf