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It is a critical task to evalaute HER2 expression level accurately for breast cancer evaluation and targeted treatment therapy selection. However, the standard multi-step Immunohistochemistry (IHC) staining is resource-intensive, expensive,…

Computer Vision and Pattern Recognition · Computer Science 2026-02-23 Peide Zhu , Linbin Lu , Zhiqin Chen , Xiong Chen

In the clinic, resected tissue samples are stained with Hematoxylin-and-Eosin (H&E) and/or Immunhistochemistry (IHC) stains and presented to the pathologists on glass slides or as digital scans for diagnosis and assessment of disease…

Computer Vision and Pattern Recognition · Computer Science 2022-04-12 Parmida Ghahremani , Joseph Marino , Ricardo Dodds , Saad Nadeem

Virtual staining streamlines traditional staining procedures by digitally generating stained images from unstained or differently stained images. While conventional staining methods involve time-consuming chemical processes, virtual…

The immunohistochemical (IHC) staining of the human epidermal growth factor receptor 2 (HER2) biomarker is widely practiced in breast tissue analysis, preclinical studies and diagnostic decisions, guiding cancer treatment and investigation…

Histological staining of tissue biopsies, especially hematoxylin and eosin (H&E) staining, serves as the benchmark for disease diagnosis and comprehensive clinical assessment of tissue. However, the process is laborious and time-consuming,…

Lymphoid infiltration at tumor margins is a key prognostic marker in solid tumors, playing a crucial role in guiding immunotherapy decisions. Current assessment methods, heavily reliant on immunohistochemistry (IHC), face challenges in…

Computer Vision and Pattern Recognition · Computer Science 2024-07-24 Zhuxian Guo , Amine Marzouki , Jean-François Emile , Henning Müller , Camille Kurtz , Nicolas Loménie

The popular use of histopathology images, such as hematoxylin and eosin (H&E), has proven to be useful in detecting tumors. However, moving such cancer cases forward for treatment requires accurate on the amount of the human epidermal…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Olaide N. Oyelade , Oliver Hoxey , Yulia Humrye

In the present study, we propose a novel case-based similar image retrieval (SIR) method for hematoxylin and eosin (H&E)-stained histopathological images of malignant lymphoma. When a whole slide image (WSI) is used as an input query, it is…

For diagnosing melanoma, hematoxylin and eosin (H&E) stained tissue slides remains the gold standard. These images contain quantitative information in different magnifications. In the present study, we investigated whether deep…

Tissues and Organs · Quantitative Biology 2019-04-15 Peizhen Xie , Ke Zuo , Yu Zhang , Fangfang Li , Mingzhu Yin , Kai Lu

Virtual stain transfer is a promising area of research in Computational Pathology, which has a great potential to alleviate important limitations when applying deeplearningbased solutions such as lack of annotations and sensitivity to a…

Computer Vision and Pattern Recognition · Computer Science 2022-10-19 Jelica Vasiljević , Friedrich Feuerhake , Cédric Wemmert , Thomas Lampert

Histopathological evaluation of tissue samples is a key practice in patient diagnosis and drug development, especially in oncology. Historically, Hematoxylin and Eosin (H&E) has been used by pathologists as a gold standard staining.…

Computer Vision and Pattern Recognition · Computer Science 2018-10-16 Amal Lahiani , Jacob Gildenblat , Irina Klaman , Shadi Albarqouni , Nassir Navab , Eldad Klaiman

Organ transplantation serves as the primary therapeutic strategy for end-stage organ failures. However, allograft rejection is a common complication of organ transplantation. Histological assessment is essential for the timely detection and…

Multiplex imaging is revolutionizing pathology by enabling the simultaneous visualization of multiple biomarkers within tissue samples, providing molecular-level insights that traditional hematoxylin and eosin (H&E) staining cannot provide.…

Image and Video Processing · Electrical Eng. & Systems 2026-01-06 Hyun-Jic Oh , Junsik Kim , Zhiyi Shi , Yichen Wu , Yu-An Chen , Peter K Sorger , Hanspeter Pfister , Won-Ki Jeong

The creation of in-silico datasets can expand the utility of existing annotations to new domains with different staining patterns in computational pathology. As such, it has the potential to significantly lower the cost associated with…

Image and Video Processing · Electrical Eng. & Systems 2024-03-12 Dominik Winter , Nicolas Triltsch , Philipp Plewa , Marco Rosati , Thomas Padel , Ross Hill , Markus Schick , Nicolas Brieu

Universal, transferable whole-slide image (WSI) representations are central to computational pathology. Incorporating multiple markers (e.g., immunohistochemistry, IHC) alongside H&E enriches H&E-based features with diverse, biologically…

Computer Vision and Pattern Recognition · Computer Science 2025-12-04 Yizhi Zhang , Lei Fan , Zhulin Tao , Donglin Di , Yang Song , Sidong Liu , Cong Cong

Histopathology, particularly hematoxylin and eosin (H\&E) staining, plays a critical role in diagnosing and characterizing pathological conditions by highlighting tissue morphology. However, H\&E-stained images inherently lack molecular…

Computational Engineering, Finance, and Science · Computer Science 2025-01-28 Qing Wang , Wen-jie Chen , Bo Li , Jing Su , Guangyu Wang , Qianqian Song

Computational analysis of multiplexed immunofluorescence histology data is emerging as an important method for understanding the tumour micro-environment in cancer. This work presents HEMIT, a dataset designed for translating Hematoxylin…

Image and Video Processing · Electrical Eng. & Systems 2024-09-30 Chang Bian , Beth Philips , Tim Cootes , Martin Fergie

While hematoxylin and eosin (H&E) is a standard staining procedure, immunohistochemistry (IHC) staining further serves as a diagnostic and prognostic method. However, acquiring special staining results requires substantial costs. Hence, we…

Computer Vision and Pattern Recognition · Computer Science 2022-08-30 Ming-Yang Ho , Min-Sheng Wu , Che-Ming Wu

Foundation models trained with self-supervised learning (SSL) on large-scale histological images have significantly accelerated the development of computational pathology. These models can serve as backbones for region-of-interest (ROI)…

Computer Vision and Pattern Recognition · Computer Science 2026-02-05 Jiawen Li , Jiali Hu , Xitong Ling , Yongqiang Lv , Yuxuan Chen , Yizhi Wang , Tian Guan , Yifei Liu , Yonghong He

The process of digitising histology slides involves multiple factors that can affect a whole slide image's (WSI) final appearance, including the staining protocol, scanner, and tissue type. This variability constitutes a domain shift and…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Manahil Raza , Saad Bashir , Talha Qaiser , Nasir Rajpoot