Andrew Janowczyk
Zitiert von
Zitiert von
Deep learning for digital pathology image analysis: A comprehensive tutorial with selected use cases
A Janowczyk, A Madabhushi
Journal of pathology informatics 7 (1), 29, 2016
Stain normalization using sparse autoencoders (StaNoSA): application to digital pathology
A Janowczyk, A Basavanhally, A Madabhushi
Computerized Medical Imaging and Graphics 57, 50-61, 2017
HistoQC: an open-source quality control tool for digital pathology slides
A Janowczyk, R Zuo, H Gilmore, M Feldman, A Madabhushi
JCO clinical cancer informatics 3, 1-7, 2019
A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue
JJ Nirschl, A Janowczyk, EG Peyster, R Frank, KB Margulies, ...
PloS one 13 (4), e0192726, 2018
Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear features from digital H&E images
X Wang, A Janowczyk, Y Zhou, R Thawani, P Fu, K Schalper, V Velcheti, ...
Scientific reports 7 (1), 1-10, 2017
Nuclear shape and orientation features from H&E images predict survival in early-stage estrogen receptor-positive breast cancers
C Lu, D Romo-Bucheli, X Wang, A Janowczyk, S Ganesan, H Gilmore, ...
Laboratory investigation 98 (11), 1438-1448, 2018
Automated tubule nuclei quantification and correlation with oncotype DX risk categories in ER+ breast cancer whole slide images
D Romo-Bucheli, A Janowczyk, H Gilmore, E Romero, A Madabhushi
Scientific reports 6 (1), 1-9, 2016
Development and evaluation of deep learning–based segmentation of histologic structures in the kidney cortex with multiple histologic stains
CP Jayapandian, Y Chen, AR Janowczyk, MB Palmer, CA Cassol, ...
Kidney international 99 (1), 86-101, 2021
A high-throughput active contour scheme for segmentation of histopathological imagery
J Xu, A Janowczyk, S Chandran, A Madabhushi
Medical image analysis 15 (6), 851-862, 2011
A resolution adaptive deep hierarchical (RADHicaL) learning scheme applied to nuclear segmentation of digital pathology images
A Janowczyk, S Doyle, H Gilmore, A Madabhushi
Computer Methods in Biomechanics and Biomedical Engineering: Imaging …, 2018
An oral cavity squamous cell carcinoma quantitative histomorphometric-based image classifier of nuclear morphology can risk stratify patients for disease-specific survival
C Lu, JS Lewis, WD Dupont, WD Plummer, A Janowczyk, A Madabhushi
Modern Pathology 30 (12), 1655-1665, 2017
Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer
J Whitney, G Corredor, A Janowczyk, S Ganesan, S Doyle, ...
BMC cancer 18 (1), 1-15, 2018
A deep learning based strategy for identifying and associating mitotic activity with gene expression derived risk categories in estrogen receptor positive breast cancers
D Romo‐Bucheli, A Janowczyk, H Gilmore, E Romero, A Madabhushi
Cytometry Part A 91 (6), 566-573, 2017
A deep learning classifier for prediction of pathological complete response to neoadjuvant chemotherapy from baseline breast DCE-MRI
K Ravichandran, N Braman, A Janowczyk, A Madabhushi
Medical imaging 2018: computer-aided diagnosis 10575, 79-88, 2018
A weighted mean shift, normalized cuts initialized color gradient based geodesic active contour model: applications to histopathology image segmentation
J Xu, A Janowczyk, S Chandran, A Madabhushi
Medical Imaging 2010: Image Processing 7623, 325-336, 2010
Biogeography of microbial bile acid transformations along the murine gut
S Marion, L Desharnais, N Studer, Y Dong, MD Notter, S Poudel, L Menin, ...
Journal of lipid research 61 (11), 1450-1463, 2020
High-throughput biomarker segmentation on ovarian cancer tissue microarrays via hierarchical normalized cuts
A Janowczyk, S Chandran, R Singh, D Sasaroli, G Coukos, MD Feldman, ...
IEEE transactions on biomedical engineering 59 (5), 1240-1252, 2011
A prognostic model for overall survival of patients with early-stage non-small cell lung cancer: a multicentre, retrospective study
C Lu, K Bera, X Wang, P Prasanna, J Xu, A Janowczyk, N Beig, M Yang, ...
The Lancet Digital Health 2 (11), e594-e606, 2020
Feature-driven local cell graph (FLocK): new computational pathology-based descriptors for prognosis of lung cancer and HPV status of oropharyngeal cancers
C Lu, C Koyuncu, G Corredor, P Prasanna, P Leo, XX Wang, ...
Medical image analysis 68, 101903, 2021
MRQy—An open‐source tool for quality control of MR imaging data
AR Sadri, A Janowczyk, R Zhou, R Verma, N Beig, J Antunes, ...
Medical physics 47 (12), 6029-6038, 2020
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20