Scott T. Doyle PhD

Scott Doyle

Scott T. Doyle
PhD

Assistant Professor

Department of Pathology and Anatomical Sciences

Jacobs School of Medicine & Biomedical Sciences


Specialty/Research Focus

Bioinformatics; Biomedical Image Analysis; Biomedical Imaging; Digital Pathology; Image Analysis; Quantitative Histology

Contact Information
Jacobs School
955 Main Street, Room 4205
Pathology and Anatomical Sciences
Buffalo, New York 14203
Phone: 716-829-2005
Fax: 716-829-2911
scottdoy@buffalo.edu



Professional Summary:

Our group specializes in building quantitative image and data analysis algorithms for biomedical datasets. For the past 9 years, I have been developing computerized methods to quantify and analyze large medical imaging datasets. These methods include data processing, object detection / segmentation, feature extraction and selection, dimensionality reduction, and classification (supervised and unsupervised).

I strongly believe in translating academic research into real-world products and services. To that end, along with my colleagues, I have worked at a start-up company to bring my work into the marketplace -- an experience that has given me great insight into the business side of academia. This experience broadened my understanding of how basic research is translated into a profitable enterprise, and I believe these lessons have made me a better engineer.

I am currently working as an Assistant Professor in the Department of Pathology & Anatomical Sciences at the University at Buffalo, where I am focused on building a teaching and research program for quantitative modeling of anatomy and cell biology. This program will introduce students of both medicine and engineering to pattern classification approaches developed in recent years, applying them to real-world clinical problems.

Education and Training:

  • Other, R Bioconductor Training Sessions, Department of Biostatistics and Bioinformatics, Roswell Park Cancer Institute (2016)
  • Other, hES Stem Cell Culture Training Program, WNYSTEM Stem Cell Culture, Banking, and Training Facility (2014)
  • Other, Optical Microscopy & Imaging in the Biomedical Sciences, Marine Biological Laboratory (2014)
  • PhD, Biomedical Engineering, Rutgers, The State University of New Jersey (2011)
  • BS, Biomedical Engineering, Rutgers, The State University of New Jersey (2006)

Employment:

  • Assistant Professor, Pathology and Anatomical Sciences, The University at Buffalo Jacobs School of Medicine & Biomedical Sciences (2014-present)
  • Technical Liason, Imaging Research Scientist, Veterans Affairs Hospital (2017–2018)
  • Director of Research, Ibris, Inc. (2011–2014)
  • Graduate Student, Biomedical Engineering, Rutgers, The State University of New Jersey Graduate School - New Brunswick (2006–2011)

Research Centers:

  • Center for Computational Research (CCR)

UB 2020 Strategic Strengths:

  • Information and Computing Technology

Grants and Sponsored Research:

  • April 2020–March 2024
    Quantitative Risk Model for Predicting Likelihood of Recurrence for Oral Cavity Cancer
    NIH
    Role: Principal Investigator
    $2,003,024
  • May 2017–May 2021
    Integration of Physical and Virtual Cadavers in a Hybrid Gross Anatomy Curriculum
    Center for Educational Innovation
    Role: Co-Investigator
    $10,000
  • September 2011–August 2012
    Decision Support System for Predicting Outcome of ER+ Breast Cancers
    National Institutes of Health
    Role: Co-Investigator
    $207,067
  • September 2007–May 2010
    Accurate and Reproducible Computerized Detection and Grading of Prostate Cancer from Histopathology
    Department of Defense
    Role: Principal Investigator
    $92,500

Patents:

  • Malignancy Diagnosis Using Content-based Image Retrieval of Tissue Histopat This invention relates to computer-aided diagnostics using content-based retrieval of histopathological image features. Specifically, the invention relates to the extraction of image features from a histopathological image based on predetermined criteria and their analysis for malignancy determination. (2012)

Journal Articles:

See all (3 more)

Abstracts:

  • Lewis S, Folmsbee J, Inglis SD, Doyle ST. (2018) Building a Hybrid Gross Anatomy Curriculum: Integration of Virtual & Cadaveric Models. (Apr)
  • Folmsbee J, Doyle ST. (2018) Active Deep Learning: Improved Training Efficiency of Convolutional Neural Networks for Tissue Classification in Oral Cavity Cancer. (Apr)
  • Johnson S, Brandwein M, Doyle ST. (2018) Registration parameter optimization for 3d tissue modeling from resected tumors cut into serial H&E slides. (Mar)
  • Therrien R, Doyle ST. (2018) Role of training data variability on classifier performance and generalizability. (Mar)
  • Johnson S, Ablove TS, Doyle ST. (2017) Macroscopic Anatomy at Microscopic Scale: Registration of Serial Sections of Histopathology for 3d. (Mar)
  • Therrien R, Mangione W, Doyle ST. (2017) Quantitative Dataset Similarity for Fusing Multi-Institutional Image Collections. (Mar)
  • Salunke SU, Ablove TS, Danforth TL, Tomaszewski JE, Doyle ST. (2017) Data-driven sampling method for building 3d anatomical models from serial histology. (Feb)
  • Doyle ST, Brandwein-Gensler MS, Tomaszewski JE. (2016) Quantification of tumor morphology via 3d histology: Application to oral cavity cancers. (Feb)
  • Doyle ST, Feldman MD, Tomaszewski JE, Shih N, Madabhushi A. (2011) Cascaded multi-class pairwise classifier (CascaMPa) for normal, cancerous, and cancer confounder classes in prostate histology. (Apr)
  • Sridhar A, Doyle ST, Madabhushi A. (2011) Boosted Spectral Embedding (BoSE): Applications to Content-Based Image Retrieval of Histopathology. (Jan)
  • Madabhushi A, Basavanhally A, Doyle ST, Agner S, Lee G. (2010) Computer-Aided Prognosis: Predicting Patient and Disease Outcome Via Multi-Modal Image Analysis. (Jan)
  • Doyle ST, Monaco J, Madabhushi A, Lindholm S, Ljung P, Ladic L, Tomaszewski JE, Feldman M. (2010) Evaluation of effects of JPEG2000 compression on a computer-aided detection system for prostate cancer on digitized histopathology. (Jan)
  • Basavanhally A, Doyle ST, Madabhushi A. (2010) Predicting Classifier Performance with a Small Training Set: Applications to Computer-Aided Diagnosis and Prognosis. (Jan)
  • Lee G, Doyle ST, Monaco J, Master SR, Feldman MD, Tomaszewski JE, Madabhushi A. (2009) 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. (Jan)
  • Naik S, Doyle ST, Agner S, Madabhushi A, Feldman MD, Tomaszewski JE. (2008) Automated gland and nuclei segmentation for grading of prostate and breast cancer histopathology. (Jan)
  • Doyle ST, Agner S, Madabhushi A, Feldman MD, Tomaszewski JE. (2008) Automated grading of breast cancer histopathology using spectral clustering with textural and architectural image features. (Jan)
  • Doyle ST, Rodriguez C, Madabhushi A, Tomaszeweski J, Feldman M. (2006) Detecting prostatic adenocarcinoma from digitized histology using a multi-scale hierarchical classification approach. (Jan)
  • Doyle ST, Madabhushi A, Feldman MD, Tomaszewski JE. (2006) A boosting cascade for automated detection of prostate cancer from digitized histology. (Jan)
See all (8 more)

Professional Memberships:

  • United States & Canadian Association of Pathologists; USCAP Academic Member (2018–present)
  • RIS2E Faculty Member; Structural Sciences Learning Center (SSLC) faculty member, University at Buffalo, Buffalo, NY (2018–present)
  • Society of Photonics and Imaging Engineers (SPIE) (2014–present)

Presentations:

  • "Predicting Early Stage Oral Cavity Cancer Recurrence Using Computational Pathology and Artificial Intelligence" City-Wide Grand Rounds Lecture; Department of Medicine; University at Buffalo (2021)
  • "Building an AI School for Pathology" PathLAKE Masterclass: Data Science for Computational Pathology; PathLAKE Center of Excellence, University of Warwick (2020)
  • "Building and Deploying Machine Learning and Deep Learning Solutions for Computational Pathology" Microcredit Course: Computational Pathology Introduction; Indian Institute of Technology Kharagpur (2020)
  • "Introduction to Machine Learning (AKA Artificial Intelligence)" Resident Lecture; Department of Pathology & Anatomical Sciences; University at Buffalo (2019)
  • "Biomedical Imaging Ontologies to Promote Interoperability of Heterogeneous Data" American Society of Nephrology (ASN) National Meeting: Kidney Week (2019)
  • "Basic Principles of Image Analysis, Segmentation, Feature Extraction" American Society of Nephrology (ASN) GlomCon Series; Computational Nephropathology: From Basics to Applications (2019)
  • "Building an AI School for Pathology: Workflow for Human-AI Interfaces" 31st European Congress of Pathology (ECP): Computational Pathology Symposium (2019)
  • "AI and Pathology in Training: Building and Explaining Algorithms to Medical Students" Histology Image Analysis (HIMA) Pathology Informatics Summit (2019)
  • "Computational Pathology and Anatomy using Traditional and Deep Machine Learning Methods" Grand Rounds; Department of Biomedical Informatics; University at Buffalo (2019)
  • "Machine Learning for the Practicing Pathologist" USCAP Workshop for Clinical Pathology (2019)
  • "Artificial Intelligence School for Pathology: Understanding Deep and Traditional Machine Learning for Oral Cavity Cancer Risk Prediction" Grand Rounds; Department of Pathology & Anatomical Sciences; University at Buffalo (2018)
  • "Computational Pathology for Risk Prediction" Seminar Series; Department of Pathology; Ichan School of Medicine, Mount Sinai Hospital (2018)
  • "Image Analysis, Graph Theory, and Machine Learning for 2D & 3D Modelling of Oral Cavity Cancer" Seminar Series; Department of Pathology; Ichan School of Medicine, Mount Sinai Hospital (2017)
  • "HistoCAD in the Prediction of Outcomes" ASIP Bioimaging Workshop; American Society for Investigative Pathology (2014)
See all (4 more)

Service Activities:

  • Prepare for and participate in LCME Accreditation Site Visits. Responsible for providing junior faculty input on medical school curriculum, education, and environment.; LCME Group Junior Faculty Representative (2019)
  • Mentor undergraduate students from under-represented groups (first-generation and low-income backgrounds) on their path to a PhD.; McNair Scholarship Program Mentor (2019–present)
  • Served as departmental representative from Pathology & Anatomical Sciences for the Ph.D. Program in Biomedical Sciences. Responsible for reviewing and leading discussions on applicants to the PPBS program. Developed PPBS curriculum changes as mandated by external reviewers.; PPBS Graduate Admissions and Steering Committee Member (2018–present)
  • Develop and implement the “Atoms to Anatomy” research direction in JSMBS and the Department of Pathology and Anatomical Sciences.; Structural Sciences Learning Center (SSLC) (2018–present)
  • March for Babies Raised over $1,000 for March of Dimes in Buffalo, NY; participated in the "March for Babies" event; Volunteer (2018–present)
  • Develop JSMBS strategic plan for research direction and school basic science policies and focus. Advertise the efforts of the strategic planning committee.; JSMBS Research Strategic Planning Committee (2017–present)
  • Responsible for reviewing, scoring, and interviewing applicants to the Department of Pathology & Anatomical Sciences.; Graduate Admissions Committee Member (Pathology & Anatomical Sciences) (2016–present)
  • Responsible for working with PAS administration to ensure that the departmental website is transitioned and maintained to new JSMBS formatting.; Website Transition Committee Member (Pathology & Anatomical Sciences) (2016–2017)
  • Mentor talented students from under-represented backgrounds who are focused on preparing for careers in STEM fields.; Collegiate Science and Technology Entry Program (CSTEP) Mentor (2016–present)
  • Responsible for reviewing, discussing, and interviewing candidates for BME junior faculty positions.; Faculty Recruitment Committee Member (Biomedical Engineering) (2016–present)
  • Responsible for reviewing, discussing, and interviewing candidates for the PAS junior faculty hires.; Faculty Recruitment Committee Member (Pathology & Anatomical Sciences) (2016–present)
  • Responsible for running and moderating speaker sessions, reviewing papers, and contributing to the conference direction for SPIE Medical Imaging: Digital Pathology Sessions; SPIE Medical Imaging Program Committee and Session Chair (2016–present)
  • Responsible for discussing and voting on matters concerning the governance of the graduate program. Also responsible for shaping the department vision for the future.; Graduate Program Steering & Executive Committee Member (Pathology & Anatomical Sciences) (2015–present)
  • Responsible for reviewing papers and moderating the Bioimaging Session at Pattern Recognition in Bioinformatics; Pattern Recognition in Bioinformatics (PRIB) Session Chair and Committee Member (2010)
  • Responsible for presenting research and fielding community questions during panel discussion and Q&A; Histology Image Analysis (HIMA) Conference Panel Member (2009–2015)
  • Peer Reviewer for Journals Human Pathology, Medical Imagine Analysis, Medical Physics, Transactions on Biomedical Engineering, BioMedCentral (BMC) Cancer, BMC Bioinformatics, Society of Photonics and Imaging Engineers (SPIE), Medical Image Computing and Computer-Assisted Intervention, International Symposium on Biomedical Imaging (ISBI); Reviewer (2007–present)

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Contact Information

Jacobs School
955 Main Street, Room 4205
Pathology and Anatomical Sciences
Buffalo, New York 14203
Phone: 716-829-2005
Fax: 716-829-2911
scottdoy@buffalo.edu