TS7B: INTRODUCTION TO IMAGE ANALYSIS AND DEEP LEARNING FOR DIGITAL PATHOLOGY

WEDNESDAY, AUGUST 21 AND THURSDAY, AUGUST 22
DAY 1: 2:05 - 6:30 PM | DAY 2: 8:30 AM - 4:20 PM

INSTRUCTORS:

Kate Lillard Tunstall, PhD, CSO, Indica Labs, Inc.

Scott M. Lawrence, Associate Scientist, Cancer Genomics Research Laboratory (CGR), Division of Cancer Epidemiology and Genetics, NCI, FNLCR, Leidos Biomedical Research

Doug Bowman, Director of Pharma Services, Indica Labs, Inc.

This training seminar will include both hands-on and lecture components designed to introduce basic digital pathology image analysis and deep learning concepts to histopathology and pathology professionals who have had limited previous exposure. In the first part of the seminar, we will cover digital pathology image analysis concepts, staining and imaging requirements, post-analysis data interpretation, typical applications and case studies. We will then take a shallow dive into deep learning in pathology and introduce you to some of the basic terminology, concepts and methods which are relevant to the pathologist’s workflow. Researchers currently using deep learning will discuss applications and clinical utility. The seminar will wrap up with a hands-on workshop (laptop required).

TOPICS TO BE DISCUSSED:

• Introduction to traditional image analysis and image management
• AI and deep learning for image analysis and computational pathology- how it works
• Input requirements for AI and how it differs from traditional image analysis
• Real expertise in image analysis in digital pathology- demonstrations of use
• Use cases for AI in molecular diagnostics
• Introduction to software and different types of networks available and how they work
• Overview of tools available for image analysis
• Hands-on assignment

INSTRUCTOR BIOGRAPHY:

Kate Lillard Tunstall, PhD, CSO, Indica Labs, Inc.

Kate Lillard received her PhD in Molecular Genetics and Biochemistry from the University of Cincinnati Medical Center, followed by a Howard Hughes postdoctoral fellowship at the University of Texas Southwestern Medical Center. While conducting research in the area of stem cell biology and oncology as a graduate and postdoctoral fellow, Dr. Lillard developed a keen interest in IHC and image analysis. Following this, she joined Aperio in 2007 where she supported and then managed image analysis products for digital pathology. After acquisition of Aperio by Leica in late 2012, Dr. Lillard joined Indica Labs as CSO where she supports, promotes, and helps guide the development of digital pathology image analysis and artificial intelligence solutions for the life sciences.

Scott M. Lawrence, Associate Scientist, Cancer Genomics Research Laboratory (CGR), Division of Cancer Epidemiology and Genetics, NCI, FNLCR, Leidos Biomedical Research

Scott is an associate scientist in the Molecular and Digital Pathology Laboratory for Leidos Biomedical Inc. The group primarily supports the Division of Cancer Epidemiology and Genetics (DCEG) of the NCI with all histopathology applications from tissue preparation though staining, imaging, and analysis. He started his career in a veterinary histopathology lab where he established digital imaging and analysis applications for preclinical work in mice and rats. Afterwards he worked with a pharmacodynamics group developing slide-based assays for phase 0 clinical trials focusing on standardizing multiplex immunofluorescent acquisition and analysis of tissue and circulating tumor cells. Scott has worked in the field for over 17 years bridging experience from the histology wet lab with digital imaging, automation, and analysis.

Doug Bowman, Director of Pharma Services, Indica Labs, Inc.

Douglas Bowman is the Vice President, Pharma Services at Indica Labs, Inc. Mr. Bowman plays an important role as the company develops its image analysis and biomarker assay services business to support preclinical and clinical biomarker assays for Indica Lab’s academic, biotech, and pharma customers. Doug was previously at Takeda Pharmaceuticals for 11 years where he was responsible for developing quantitative biomarker assays to support the Oncology Discovery and Translational Research groups. He was a key contributor to the development of a high throughput, automated, IHC biomarker laboratory that integrated a sample management system, digital slide scanners, and quantitative image analysis into the research workflow.

Training Seminar Information

Each CHI Training Seminar offers 1.5 days of instruction with start and stop times for each day shown above and on the Event-at-a-Glance published in the onsite Program & Event Guide. Training Seminars will include morning and afternoon refreshment breaks, as applicable, and lunch will be provided to all registered attendees on the full day of the class.

Each person registered specifically for the Training Seminar will be provided with a hard copy handbook for the seminar in which they are registered. A limited number of additional handbooks will be available for other delegates who wish to attend the seminar, but after these have been distributed, no additional books will be available.

Though CHI encourages track hopping between conference programs, we ask that Training Seminars not be disturbed once they have begun. In the interest of maintaining the highest quality learning environment for Training Seminar attendees, and because seminars are conducted differently than conference programming, we ask that attendees commit to attending the entire program, and not engage in track hopping, as to not disturb the hands-on style instruction being offered to the other participants.