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ArticlesPeer ReviewedFull Text
Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases
Author / Creator:Janowczyk, Andrew ; Madabhushi, Anant
Publisher:United States: Elsevier Inc
Journal title:Journal of pathology informatics, 2016-01, Vol.7 (1), p.29-29, Article 29
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ArticlesPeer ReviewedFull Text
Nuclear shape and orientation features from H&E images predict survival in early-stage estrogen receptor-positive breast cancers
Author / Creator:Lu, Cheng ; Romo-Bucheli, David ; Wang, Xiangxue ; Janowczyk, Andrew ; Ganesan, Shridar ; Gilmore, Hannah ; Rimm, David ; Madabhushi, Anant
Publisher:New York: Elsevier Inc
Journal title:Laboratory investigation, 2018-11, Vol.98 (11), p.1438-1448
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ArticlesPeer ReviewedFull Text
Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer
Author / Creator:Whitney, Jon ; Corredor, German ; Janowczyk, Andrew ; Ganesan, Shridar ; Doyle, Scott ; Tomaszewski, John ; Feldman, Michael ; Gilmore, Hannah ; Madabhushi, Anant
Publisher:England: BioMed Central Ltd
Journal title:BMC cancer, 2018-05, Vol.18 (1), p.610-610, Article 610
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ArticlesPeer ReviewedFull Text
Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear features from digital H&E images
Author / Creator:Wang, Xiangxue ; Janowczyk, Andrew ; Zhou, Yu ; Thawani, Rajat ; Fu, Pingfu ; Schalper, Kurt ; Velcheti, Vamsidhar ; Madabhushi, Anant
Publisher:London: Nature Publishing Group UK
Journal title:Scientific reports, 2017-10, Vol.7 (1), p.13543-10, Article 13543
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ArticlesPeer ReviewedFull Text
Quick Annotator: an open‐source digital pathology based rapid image annotation tool
Author / Creator:Miao, Runtian ; Toth, Robert ; Zhou, Yu ; Madabhushi, Anant ; Janowczyk, Andrew
Publisher:Hoboken, USA: John Wiley & Sons, Inc
Journal title:The journal of pathology. Clinical research, 2021-11, Vol.7 (6), p.542-547
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PatchSorter: a high throughput deep learning digital pathology tool for object labeling
Author / Creator:Walker, Cédric ; Talawalla, Tasneem ; Toth, Robert ; Ambekar, Akhil ; Rea, Kien ; Chamian, Oswin ; Fan, Fan ; Berezowska, Sabina ; Rottenberg, Sven ; Madabhushi, Anant ; Maillard, Marie ; Barisoni, Laura ; Horlings, Hugo Mark ; Janowczyk, Andrew
Publisher:London: Nature Publishing Group UK
Journal title:NPJ digital medicine, 2024-06, Vol.7 (1), p.164-7, Article 164
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ArticlesPeer ReviewedFull Text
Impact of scanner variability on lymph node segmentation in computational pathology
Author / Creator:Khan, Amjad ; Janowczyk, Andrew ; Müller, Felix ; Blank, Annika ; Nguyen, Huu Giao ; Abbet, Christian ; Studer, Linda ; Lugli, Alessandro ; Dawson, Heather ; Thiran, Jean-Philippe ; Zlobec, Inti
Publisher:United States: Elsevier Inc
Journal title:Journal of pathology informatics, 2022-01, Vol.13, p.100127, Article 100127
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ArticlesPeer ReviewedFull Text
Characterization of arteriosclerosis based on computer-aided measurements of intra-arterial thickness
Author / Creator:Zhou, Jin ; Li, Xiang ; Demeke, Dawit ; Dinh, Timothy A. ; Yang, Yingbao ; Janowczyk, Andrew R. ; Zee, Jarcy ; Holzman, Lawrence ; Mariani, Laura ; Chakrabarty, Krishnendu ; Barisoni, Laura ; Hodgin, Jeffrey B. ; Lafata, Kyle J.
Publisher:United States: Society of Photo-Optical Instrumentation Engineers
Journal title:Journal of medical imaging (Bellingham, Wash.), 2024-09, Vol.11 (5), p.057501-057501
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MMO-Net (Multi-Magnification Organ Network): A use case for Organ Identification using Multiple Magnifications in Preclinical Pathology Studies
Author / Creator:Gámez Serna, Citlalli ; Romero-Palomo, Fernando ; Arcadu, Filippo ; Funk, Jürgen ; Schumacher, Vanessa ; Janowczyk, Andrew
Publisher:United States: Elsevier Inc
Journal title:Journal of pathology informatics, 2022-01, Vol.13, p.100126, Article 100126
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ArticlesPeer ReviewedFull Text
Engineering the future of 3D pathology
Author / Creator:Liu, Jonathan TC ; Chow, Sarah SL ; Colling, Richard ; Downes, Michelle R ; Farré, Xavier ; Humphrey, Peter ; Janowczyk, Andrew ; Mirtti, Tuomas ; Verrill, Clare ; Zlobec, Inti ; True, Lawrence D
Publisher:Hoboken, USA: John Wiley & Sons, Inc
Journal title:The journal of pathology. Clinical research, 2024-01, Vol.10 (1), p.e347-n/a
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ArticlesPeer ReviewedFull Text
Computational pathology improves risk stratification of a multi-gene assay for early stage ER+ breast cancer
Author / Creator:Chen, Yuli ; Li, Haojia ; Janowczyk, Andrew ; Toro, Paula ; Corredor, Germán ; Whitney, Jon ; Lu, Cheng ; Koyuncu, Can F. ; Mokhtari, Mojgan ; Buzzy, Christina ; Ganesan, Shridar ; Feldman, Michael D. ; Fu, Pingfu ; Corbin, Haley ; Harbhajanka, Aparna ; Gilmore, Hannah ; Goldstein, Lori J. ; Davidson, Nancy E. ; Desai, Sangeeta ; Parmar, Vani ; Madabhushi, Anant
Publisher:London: Nature Publishing Group UK
Journal title:NPJ breast cancer, 2023-05, Vol.9 (1), p.40-40, Article 40
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ArticlesPeer ReviewedFull Text
Quantifying local heterogeneity via morphologic scale: Distinguishing tumoral from stromal regions
Author / Creator:Janowczyk, Andrew ; Chandran, Sharat ; Madabhushi, Anant
Publisher:India: Elsevier Inc
Journal title:Journal of pathology informatics, 2013, Vol.4 (2), p.8-S8, Article 8
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ArticlesPeer ReviewedFull Text
Update on the current opinion, status and future development of digital pathology in Switzerland in light of COVID-19
Author / Creator:Koelzer, Viktor Hendrik ; Grobholz, Rainer ; Zlobec, Inti ; Janowczyk, Andrew
Publisher:England: BMJ Publishing Group Ltd and Association of Clinical Pathologists
Journal title:Journal of clinical pathology, 2022-10, Vol.75 (10), p.687-689
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ArticlesPeer ReviewedFull Text
A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H E tissue
Author / Creator:Jeffrey J Nirschl ; Andrew Janowczyk ; Eliot G Peyster ; Renee Frank ; Kenneth B Margulies ; Michael D Feldman ; Anant Madabhushi
Publisher:Public Library of Science (PLoS)
Journal title:PloS one, 2018-04, Vol.13 (4), p.e0192726
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ArticlesPeer ReviewedFull Text
Current opinion, status and future development of digital pathology in Switzerland
Author / Creator:Unternaehrer, Julia ; Grobholz, Rainer ; Janowczyk, Andrew ; Zlobec, Inti
Publisher:England: BMJ Publishing Group Ltd and Association of Clinical Pathologists
Journal title:Journal of clinical pathology, 2020-06, Vol.73 (6), p.341-346
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ArticlesPeer ReviewedFull Text
Automated Tubule Nuclei Quantification and Correlation with Oncotype DX risk categories in ER+ Breast Cancer Whole Slide Images
Author / Creator:Romo-Bucheli, David ; Janowczyk, Andrew ; Gilmore, Hannah ; Romero, Eduardo ; Madabhushi, Anant
Publisher:London: Nature Publishing Group UK
Journal title:Scientific reports, 2016-09, Vol.6 (1), p.32706-32706, Article 32706
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ArticlesPeer ReviewedFull Text
Meta-omics-aided isolation of an elusive anaerobic arsenic-methylating soil bacterium
Author / Creator:Viacava, Karen ; Qiao, Jiangtao ; Janowczyk, Andrew ; Poudel, Suresh ; Jacquemin, Nicolas ; Meibom, Karin Lederballe ; Shrestha, Him K. ; Reid, Matthew C. ; Hettich, Robert L. ; Bernier-Latmani, Rizlan
Publisher:London: Nature Publishing Group UK
Journal title:The ISME Journal, 2022-07, Vol.16 (7), p.1740-1749
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ArticlesPeer ReviewedFull Text
A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue
Author / Creator:Nirschl, Jeffrey J. ; Janowczyk, Andrew ; Peyster, Eliot G. ; Frank, Renee ; Margulies, Kenneth B. ; Feldman, Michael D. ; Madabhushi, Anant
Publisher:United States: Public Library of Science
Journal title:PloS one, 2018-04, Vol.13 (4), p.e0192726-e0192726
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An oral cavity squamous cell carcinoma quantitative histomorphometric-based image classifier of nuclear morphology can risk stratify patients for disease-specific survival
Author / Creator:Lu, Cheng ; Lewis, James S ; Dupont, William D ; Plummer, W Dale ; Janowczyk, Andrew ; Madabhushi, Anant
Publisher:New York: Nature Publishing Group US
Journal title:Modern pathology, 2017-12, Vol.30 (12), p.1655-1665
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T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learning–derived estimates of epithelium, lumen, and stromal composition on corresponding whole mount hi...
Author / Creator:Shiradkar, Rakesh ; Panda, Ananya ; Leo, Patrick ; Janowczyk, Andrew ; Farre, Xavier ; Janaki, Nafiseh ; Li, Lin ; Pahwa, Shivani ; Mahran, Amr ; Buzzy, Christina ; Fu, Pingfu ; Elliott, Robin ; MacLennan, Gregory ; Ponsky, Lee ; Gulani, Vikas ; Madabhushi, Anant
Publisher:Berlin/Heidelberg: Springer Berlin Heidelberg
Journal title:European radiology, 2021-03, Vol.31 (3), p.1336-1346
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Showing 1 to 20 of 38 results

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Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases

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Nuclear shape and orientation features from H&E images predict survival in early-stage estrogen receptor-positive breast cancers

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Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer

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Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear features from digital H&E images

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Quick Annotator: an open‐source digital pathology based rapid image annotation tool

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PatchSorter: a high throughput deep learning digital pathology tool for object labeling

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Impact of scanner variability on lymph node segmentation in computational pathology

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Characterization of arteriosclerosis based on computer-aided measurements of intra-arterial thickness

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MMO-Net (Multi-Magnification Organ Network): A use case for Organ Identification using Multiple Magnifications in Preclinical Pathology Studies

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Engineering the future of 3D pathology

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Computational pathology improves risk stratification of a multi-gene assay for early stage ER+ breast cancer

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Quantifying local heterogeneity via morphologic scale: Distinguishing tumoral from stromal regions

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Update on the current opinion, status and future development of digital pathology in Switzerland in light of COVID-19

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A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H E tissue

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Current opinion, status and future development of digital pathology in Switzerland

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Automated Tubule Nuclei Quantification and Correlation with Oncotype DX risk categories in ER+ Breast Cancer Whole Slide Images

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Meta-omics-aided isolation of an elusive anaerobic arsenic-methylating soil bacterium

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A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue

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An oral cavity squamous cell carcinoma quantitative histomorphometric-based image classifier of nuclear morphology can risk stratify patients for disease-specific survival

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T1 and T2 MR fingerprinting measurements of prostate cancer and prostatitis correlate with deep learning–derived estimates of epithelium, lumen, and stromal composition on corresponding whole mount hi...

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