Nuclei Instance Segmentation and Classification in Histopathology Images with Stardist [PDF]
2022 IEEE International Symposium on Biomedical Imaging Challenges (ISBIC), 2022 Instance segmentation and classification of nuclei is an impor-tant task in computational pathology. We show that StarDist, a deep learning nuclei segmentation method originally devel-oped for fluorescence microscopy, can be extended and suc-cessfully ...
Martin Weigert, Uwe Schmidt
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Joint and individual analysis of breast cancer histologic images and genomic covariates [PDF]
, 2020 A key challenge in modern data analysis is understanding connections between complex and differing modalities of data. For example, two of the main approaches to the study of breast cancer are histopathology (analyzing visual characteristics of tumors ...
Calhoun, Benjamin C. +10 more
core +3 more sources
Scaling Self-Supervised Learning for Histopathology with Masked Image Modeling
medRxiv, 2023 Computational pathology is revolutionizing the field of pathology by integrating advanced computer vision and machine learning technologies into diagnostic workflows.
Alexandre Filiot +7 more
semanticscholar +1 more source
A Morphology Focused Diffusion Probabilistic Model for Synthesis of Histopathology Images [PDF]
IEEE Workshop/Winter Conference on Applications of Computer Vision, 2022 Visual microscopic study of diseased tissue by pathologists has been the cornerstone for cancer diagnosis and prognostication for more than a century. Recently, deep learning methods have made significant advances in the analysis and classification of ...
Puria Azadi Moghadam +6 more
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Journal of Skin Cancer, 2022 Context. Keratinocyte carcinomas are the most common malignant condition in Caucasian populations. African albinos have hypomelanized sensitive skin that is quite susceptible to photocarcinogenesis. Of the keratinocyte carcinomas, squamous cell carcinoma
Nnaemeka T. Onyishi, Samuel R. Ohayi
doaj +1 more source
Serial optical coherence microscopy for label-free volumetric histopathology [PDF]
, 2020 The observation of histopathology using optical microscope is an essential procedure for examination of tissue biopsies or surgically excised specimens in biological and clinical laboratories.
A Azaripour +33 more
core +1 more source
Pathomic Fusion: An Integrated Framework for Fusing Histopathology and Genomic Features for Cancer Diagnosis and Prognosis [PDF]
IEEE Transactions on Medical Imaging, 2019 Cancer diagnosis, prognosis, mymargin and therapeutic response predictions are based on morphological information from histology slides and molecular profiles from genomic data.
Richard J. Chen +6 more
semanticscholar +1 more source
IEEE Access, 2022 Cancer accounts for a huge mortality rate due to its aggressiveness, colossal potential of metastasis, and heterogeneity (causing resistance against chemotherapy).
S. Mehmood +6 more
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Frequency and clinicopathological characteristics of variants of primary focal segmental glomerulosclerosis in adults presenting with nephrotic syndrome [PDF]
Journal of Nephropathology, 2013 Background: There is no information on the frequency and clinicopathological presentation of the variants of primary focal segmental glomerulosclerosis (FSGS) in adults presenting with idiopathic nephrotic syndrome (INS) in Pakistan.
Shaheera Shakeel +4 more
doaj +1 more source
Next-Generation Morphometry for pathomics-data mining in histopathology
Nature Communications, 2023 Pathology diagnostics still rely on tissue morphology assessment by trained experts. Here, the authors perform deep-learning-based segmentation followed by large-scale feature extraction of histological images, i.e., next-generation morphometry, to ...
David L. Hölscher +16 more
semanticscholar +1 more source