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20192024
most citedTranscriptome-wide prediction of prostate cancer gene expression from histopathology images using co-expression based convolutional neural networks

31 citations · 95 across the 11 of their papers we have counts for

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6 papers · 1 filter

eess.IV2024

A Mixture of Experts (MoE) model to improve AI-based computational pathology prediction performance under variable levels of histopathology image blur

Yujie Xiang, Bojing Liu, Mattias Rantalainen

AI-based models for histopathology whole slide image (WSI) analysis are increasingly common, but unsharp or blurred areas within WSI can significantly reduce prediction performance…

eess.IV2024★ 1 cited

WEEP: A method for spatial interpretation of weakly supervised CNN models in computational pathology

Abhinav Sharma, Bojing Liu, Mattias Rantalainen

Deep learning enables the modelling of high-resolution histopathology whole-slide images (WSI). Weakly supervised learning of tile-level data is typically applied for tasks where l…

eess.IV2023★ 23 cited

The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue

Philippe Weitz, Masi Valkonen, Leslie Solorzano +38

The alignment of tissue between histopathological whole-slide-images (WSI) is crucial for research and clinical applications. Advances in computing, deep learning, and availability…

eess.IV2022★ 4 cited

ACROBAT -- a multi-stain breast cancer histological whole-slide-image data set from routine diagnostics for computational pathology

Philippe Weitz, Masi Valkonen, Leslie Solorzano +15

The analysis of FFPE tissue sections stained with haematoxylin and eosin (H&E) or immunohistochemistry (IHC) is an essential part of the pathologic assessment of surgically resecte…

eess.IV2021

Using deep learning to detect patients at risk for prostate cancer despite benign biopsies

Bojing Liu, Yinxi Wang, Philippe Weitz +6

Background: Transrectal ultrasound guided systematic biopsies of the prostate is a routine procedure to establish a prostate cancer diagnosis. However, the 10-12 prostate core biop…

eess.IV2020★ 6 cited

Predicting molecular phenotypes from histopathology images: a transcriptome-wide expression-morphology analysis in breast cancer

Yinxi Wang, Kimmo Kartasalo, Masi Valkonen +4

Molecular phenotyping is central in cancer precision medicine, but remains costly and standard methods only provide a tumour average profile. Microscopic morphological patterns obs…