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ORCIDScott Doyle
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2020 – today
- 2023
[c31]Matthew A. Wysocki, Scott Doyle:
Advancing finite element analysis of osteological structures in biomedical research. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2023- [c30]Steven A. Lewis, Scott Doyle:
Attention-guided single-voxel attacks for 3-dimensional neural networks: experiments with post-mortem CT segmentation. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2023 - 2022
- [c29]Matthew A. Wysocki, Scott Doyle:
Generating statistical shape models of osteological structure from cadaveric CT data. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2022 - 2021
- [c28]Dhadma Balachandran, Margaret Brandwein-Weber, Jonathan Folmsbee, Scott Doyle:
Comparing architectural features between heuristically human-annotated and Artificial Intelligence (AI) generated tumor and satellite labels in early-stage oral cavity cancer. Medical Imaging: Digital Pathology 2021 - [c27]Jonathan Folmsbee, Margaret Brandwein-Weber, Scott Doyle:
Whole slide semantic segmentation: large scale active learning for digital pathology. Medical Imaging: Digital Pathology 2021 - [c26]Gouthamrajan Nadarajan, Scott Doyle:
Conditional generative adversarial networks for H&E to IF domain transfer: experiments with breast and prostate cancer. Medical Imaging: Digital Pathology 2021 - 2020
- [c25]Gouthamrajan Nadarajan, Scott Doyle:
Realistic cross-domain microscopy via conditional generative adversarial networks: converting immunofluorescence to hematoxylin and eosin. Medical Imaging: Digital Pathology 2020: 113200S
2010 – 2019
- 2019
- [c24]Sylvester Sakilay, Danne C. Elbers, Scott Doyle, Luis E. Selva, Brett R. Johnson, Nhan V. Do, Peter L. Elkin:
Workflow Pipeline for Medical Image Data Curation and Sharing. AMIA 2019 - [c23]Gouthamrajan Nadarajan, Tyna A. Hope, Dan Wang, Alison Cheung, Fiona Ginty, Martin J. Yaffe, Scott Doyle:
Automated multi-class ground-truth labeling of H&E images for deep learning using multiplexed fluorescence microscopy. Medical Imaging: Digital Pathology 2019: 109560J - [c22]Chen-Yu Sun, Weiguo Liu, Scott Doyle:
Two-tier classifier for identifying small objects in histological tissue classification: experiments with colon cancer tissue mapping. Medical Imaging: Digital Pathology 2019: 109560F - [c21]Jonathan Folmsbee, Starr Johnson, Xulei Liu, Margaret Brandwein-Weber, Scott Doyle:
Fragile neural networks: the importance of image standardization for deep learning in digital pathology. Medical Imaging: Digital Pathology 2019: 1095613 - 2018
- [j6]Andrew Janowczyk, Scott Doyle, Hannah Gilmore, Anant Madabhushi
:
A resolution adaptive deep hierarchical (RADHicaL) learning scheme applied to nuclear segmentation of digital pathology images. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 6(3): 270-276 (2018) - [c20]Danne C. Elbers, Frank Meng, Scott Doyle, Sylvester Sakilay, Sung Feng-Chi, Brett R. Johnson, Robert B. Hall, Nathanael Fillmore, Daniel Chen, Alexander D. Diehl, Samuel Ajjarapu, Karen E. Pierce-Murray, Corri DeDomenico, Colleen Shannon, Sara Schiller, Nhan V. Do, Peter L. Elkin, Louis D. Fiore, Mary T. Brophy:
The Implementation of the Precision Oncology Data Repository in the Veterans Affairs Healthcare System. AMIA 2018 - [c19]Jonathan Folmsbee, Xulei Liu, Margaret Brandwein-Weber, Scott Doyle:
Active deep learning: Improved training efficiency of convolutional neural networks for tissue classification in oral cavity cancer. ISBI 2018: 770-773 - [c18]Ryan Therrien, Scott Doyle:
Role of training data variability on classifier performance and generalizability. Medical Imaging: Digital Pathology 2018: 1058109 - 2017
- [j5]Metin N. Gurcan, John Tomaszewski, James A. Overton, Scott Doyle, Alan Ruttenberg, Barry Smith:
Developing the Quantitative Histopathology Image Ontology (QHIO): A case study using the hot spot detection problem. J. Biomed. Informatics 66: 129-135 (2017) - [c17]Snehal Ulhas Salunke, Tova Ablove, Theresa Danforth, John Tomaszewski, Scott Doyle:
Data-driven sampling method for building 3D anatomical models from serial histology. Medical Imaging: Digital Pathology 2017: 1014005 - 2016
- [c16]Somayeh B. Shafiei, Scott Doyle, Khurshid A. Guru:
Mentor's brain functional connectivity network during robotic assisted surgery mentorship. EMBC 2016: 1717-1720 - [c15]Scott Doyle, Margaret Brandwein-Gensler, John Tomaszewski:
Quantification of tumor morphology via 3D histology: application to oral cavity cancers. Medical Imaging: Digital Pathology 2016: 979112 - 2012
- [j4]Scott Doyle, Michael D. Feldman, Natalie Shih, John Tomaszewski, Anant Madabhushi:
Cascaded discrimination of normal, abnormal, and confounder classes in histopathology: Gleason grading of prostate cancer. BMC Bioinform. 13: 282 (2012) - [j3]Scott Doyle, Michael D. Feldman, John Tomaszewski, Anant Madabhushi:
A Boosted Bayesian Multiresolution Classifier for Prostate Cancer Detection From Digitized Needle Biopsies. IEEE Trans. Biomed. Eng. 59(5): 1205-1218 (2012) - 2011
- [j2]Scott Doyle, James Monaco, Michael D. Feldman, John Tomaszewski, Anant Madabhushi:
An Active Learning Based Classification Strategy for the Minority Class Problem: Application to Histopathology Annotation. BMC Bioinform. 12: 424 (2011) - [j1]Anant Madabhushi, Shannon Agner, Ajay Basavanhally, Scott Doyle, George Lee:
Computer-aided prognosis: Predicting patient and disease outcome via quantitative fusion of multi-scale, multi-modal data. Comput. Medical Imaging Graph. 35(7-8): 506-514 (2011) - [c14]Scott Doyle, Michael D. Feldman, John Tomaszewski, Natalie Shih, Anant Madabhushi:
Cascaded multi-class pairwise classifier (CascaMPa) for normal, cancerous, and cancer confounder classes in prostate histology. ISBI 2011: 715-718 - [c13]Akshay Sridhar, Scott Doyle, Anant Madabhushi:
Boosted Spectral Embedding (BoSE): Applications to content-based image retrieval of histopathology. ISBI 2011: 1897-1900 - 2010
- [c12]Ajay Basavanhally, Scott Doyle, Anant Madabhushi:
Predicting classifier performance with a small training set: applications to computer-aided diagnosis and prognosis. ISBI 2010: 229-232 - [c11]Scott Doyle, James Monaco, Anant Madabhushi, Stefan Lindholm, Patric Ljung, Lance Ladic, John Tomaszewski, Michael D. Feldman:
Evaluation of effects of jpeg2000 compression on a computer-aided detection system for prostate cancer on digitized histopathology. ISBI 2010: 1313-1316 - [c10]Anant Madabhushi, Ajay Basavanhally, Scott Doyle, Shannon Agner, George Lee:
Computer-aided prognosis: predicting patient and disease outcome via multi-modal image analysis. ISBI 2010: 1415-1418 - [c9]Scott Doyle, Anant Madabhushi:
Consensus of Ambiguity: Theory and Application of Active Learning for Biomedical Image Analysis. PRIB 2010: 313-324
2000 – 2009
- 2009
- [c8]George Lee, Scott Doyle, James Monaco, Michael D. Feldman, Stephen R. Master, John Tomaszewski, Anant Madabhushi:
A Knowledge Representation Framework for Integration, Classification of Multi-Scale Imaging and Non-Imaging Data: Preliminary Results in Predicting Prostate Cancer Recurrence by Fusing Mass Spectrometry and Histology. ISBI 2009: 77-80 - [c7]Jay Naik, Scott Doyle, Ajay Basavanhally, Shridar Ganesan, Michael D. Feldman, John E. Tomaszewski, Anant Madabhushi:
A boosted distance metric: application to content based image retrieval and classification of digitized histopathology. Medical Imaging: Computer-Aided Diagnosis 2009: 72603F - [c6]Robert Toth, Scott Doyle, Mark Rosen, Arjun Kalyanpur, Sona Pungavkar, B. Nicolas Bloch, Elizabeth Genega, Neil Rofsky, Robert E. Lenkinski, Anant Madabhushi:
WERITAS: weighted ensemble of regional image textures for ASM segmentation. Medical Imaging: Image Processing 2009: 725905 - 2008
- [c5]Shivang Naik, Scott Doyle, Shannon Agner, Anant Madabhushi, Michael D. Feldman, John Tomaszewski:
Automated gland and nuclei segmentation for grading of prostate and breast cancer histopathology. ISBI 2008: 284-287 - [c4]Scott Doyle, Shannon Agner, Anant Madabhushi, Michael D. Feldman, John Tomaszewski:
Automated grading of breast cancer histopathology using spectral clusteringwith textural and architectural image features. ISBI 2008: 496-499 - 2007
- [c3]Scott Doyle, Mark I. Hwang, Kinsuk Shah, Anant Madabhushi, Michael D. Feldman, John E. Tomaszeweski:
Automated Grading of Prostate Cancer Using Architectural and Textural Image Features. ISBI 2007: 1284-1287 - 2006
- [c2]Scott Doyle, Carlos Rodriguez, Anant Madabhushi, John E. Tomaszewski, Michael D. Feldman:
Detecting Prostatic Adenocarcinoma From Digitized Histology Using a Multi-Scale Hierarchical Classification Approach. EMBC 2006: 4759-4762 - [c1]Scott Doyle, Anant Madabhushi, Michael D. Feldman, John E. Tomaszeweski:
A Boosting Cascade for Automated Detection of Prostate Cancer from Digitized Histology. MICCAI (2) 2006: 504-511
Coauthor Index
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