Andrew Janowczyk
Orcid: 0000-0003-2982-4321
According to our database1,
Andrew Janowczyk
authored at least 22 papers
between 2008 and 2024.
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Bibliography
2024
PatchSorter: a high throughput deep learning digital pathology tool for object labeling.
npj Digit. Medicine, 2024
HoverFast: an accurate, high-throughput, clinically deployable nuclear segmentation tool for brightfield digital pathology images.
J. Open Source Softw., 2024
2023
Multi-site cross-organ calibrated deep learning (MuSClD): Automated diagnosis of non-melanoma skin cancer.
Medical Image Anal., 2023
CohortFinder: an open-source tool for data-driven partitioning of biomedical image cohorts to yield robust machine learning models.
CoRR, 2023
Spatial connectivity of tumor and associated cells (SpaCell): a novel computational pathology biomarker.
Proceedings of the Medical Imaging 2023: Digital and Computational Pathology, 2023
2021
Feature-driven local cell graph (FLocK): New computational pathology-based descriptors for prognosis of lung cancer and HPV status of oropharyngeal cancers.
Medical Image Anal., 2021
2020
Three-dimensional histo-morphometric features from light sheet microscopy images result in improved discrimination of benign from malignant glands in prostate cancer.
Proceedings of the Medical Imaging 2020: Digital Pathology, 2020
Computationally derived cytological image markers for predicting risk of relapse in acute myeloid leukemia patients following bone marrow transplantation.
Proceedings of the Medical Imaging 2020: Digital Pathology, 2020
2018
A resolution adaptive deep hierarchical (RADHicaL) learning scheme applied to nuclear segmentation of digital pathology images.
Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2018
Combination of nuclear NF-κB/p65 localization and gland morphological features from surgical specimens appears to be predictive of early biochemical recurrence in prostate cancer patients.
Proceedings of the Medical Imaging 2018: Digital Pathology, 2018
A deep learning classifier for prediction of pathological complete response to neoadjuvant chemotherapy from baseline breast DCE-MRI.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
2017
Stain Normalization using Sparse AutoEncoders (StaNoSA): Application to digital pathology.
Comput. Medical Imaging Graph., 2017
Proceedings of the Deep Learning for Medical Image Analysis, 1st Edition, 2017
2016
Automated tubule nuclei quantification and correlation with oncotype DX risk categories in ER+ breast cancer whole slide images.
Proceedings of the Medical Imaging 2016: Digital Pathology, San Diego, California, United States, 27 February, 2016
2012
High-Throughput Biomarker Segmentation on Ovarian Cancer Tissue Microarrays via Hierarchical Normalized Cuts.
IEEE Trans. Biomed. Eng., 2012
2011
A high-throughput active contour scheme for segmentation of histopathological imagery.
Medical Image Anal., 2011
Local morphologic scale: application to segmenting tumor infiltrating lymphocytes in ovarian cancer TMAs.
Proceedings of the Medical Imaging 2011: Image Processing, 2011
2010
A weighted mean shift, normalized cuts initialized color gradient based geodesic active contour model: applications to histopathology image segmentation.
Proceedings of the Medical Imaging 2010: Image Processing, 2010
High-Throughput Prostate Cancer Gland Detection, Segmentation, and Classification from Digitized Needle Core Biopsies.
Proceedings of the Prostate Cancer Imaging. Computer-Aided Diagnosis, 2010
2009
Hierarchical Normalized Cuts: Unsupervised Segmentation of Vascular Biomarkers from Ovarian Cancer Tissue Microarrays.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2009
2008
Proceedings of the Sixth Indian Conference on Computer Vision, Graphics & Image Processing, 2008