Automated Detection and Gleason Grading of Prostate Cancer in Digital Pathology
Automated Detection And Gleason Grading Of Prostate Cancer In Digital Pathology
Date: 8 Septemer 2021
Time: 8:00 – 9:00 PST | 11:00 – 12:00 EST | 4:00 PM BST – 5:00 PM BST
Digital pathology provides an advantage of automatizing many routine pathological tasks via computational algorithms and tools. The reporting of prostate cases is time-consuming due to a large number of slides per case. Moreover, tumor aggressivity grading (Gleason score) is well known for its subjective nature and high levels of interobserver variability. In this webinar, we will demonstrate a deep learning-based tool developed for the detection of prostate cancer in histological slides (prostate biopsies and prostatectomy specimens) and its histological grading (Gleason grading). We will present the results of the actual validation study showing high levels of accuracy in both tasks. We will discuss the practical aspects of the implementation of such tools in the diagnostic routine.
learn how to
- Learn how HALO and HALO AI were used to develop algorithms for detection of prostate cancer and Gleason grading
- Learn about the validation study to evaluate accuracy of detection and grading
- Learn about practical considerations of clinical implementation
This webinar is ideal for cancer researchers, pathologists, attending physicians, image analysts, and others working in digital pathology.
Priv.-Doz., Dr., FOA Uropathology and Digital Pathology
Institute of Pathology of the University Hospital Cologne, Germany
Yuri Tolkach is a senior attending physician in the Institute of Pathology of the University Hospital Cologne, Germany. He is the Head of Urological Pathology and of the Digital Pathology divisions. His research focuses on developing artificial intelligence-based tools for digital pathology, quality control in digital pathology, and molecular characterization of uro-oncological diseases. During his research, Yuri developed a tool for prostate cancer detection and Gleason grading in histological slides with high accuracy.
Kate Lillard Tunstall, PhD
Chief Scientific Officer
Kate Lillard received her Ph.D. 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 which led to her joining 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 Chief Scientific Officer where she supports, promotes, and helps guide the development of digital pathology image analysis solutions for the life sciences.