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BEGIN:VEVENT
DTSTAMP:20260310T125837Z
DTSTART;VALUE=DATE-TIME:20250303T140000
DTEND;VALUE=DATE-TIME:20250303T150000
SUMMARY:TIA Centre Seminar Series: Zhilong Weng (University Hospital Colo
 gne)
TZID:Europe/London
UID:20250303-8ac672c69481e10101948d8897452df5@warwick.ac.uk
CREATED:20250123T092447Z
DESCRIPTION:Title: GrandQC: A comprehensive solution to quality control p
 roblem in digital pathology Abstract: Histological slides contain numero
 us artifacts that can significantly deteriorate the performance of image
  analysis algorithms. Here we develop the GrandQC tool for tissue and mu
 lti-class artifact segmentation. GrandQC allows for high-precision tissu
 e segmentation (Dice score 0.957) and segmentation of tissue without art
 ifacts (Dice score 0.919–0.938 dependent on magnification). Slides from 
 19 international pathology departments digitized with the most common sc
 anning systems and from The Cancer Genome Atlas dataset were used to est
 ablish a QC benchmark\, analyzing inter-institutional\, intra-institutio
 nal\, temporal\, and inter-scanner slide quality variations. GrandQC imp
 roves the performance of downstream image analysis algorithms. We open-s
 ource the GrandQC tool\, our large manually annotated test dataset\, and
  all QC masks for the entire TCGA cohort to address the problem of QC in
  digital/computational pathology. GrandQC can be used as a tool to monit
 or sample preparation and scanning quality in pathology departments and 
 help to track and eliminate major artifact sources. Bio: Z. Weng is a Ph
 D student at the University of Cologne and the University Hospital Colog
 ne\, supervised by Yuri Tolkach. He got his master’s degree in Computati
 onal Engineering from the Technical University of Darmstadt in Germany\,
  where he focused on computer vision research\, including traditional im
 age processing and deep learning-based image detection. His current rese
 arch focuses on advancing artificial intelligence applications in comput
 ational pathology. Paper Link: GrandQC: A comprehensive solution to qual
 ity control problem in digital pathology | Nature Communications How to 
 attend: Either turn up to the event on the day\, or if you want to atten
 d online then please contact Adam Shephard (adam.shephard@warwick.ac.uk)
  for more details.
LOCATION:CS 1.04
URL:https://warwick.ac.uk/fac/cross_fac/tia/seminars/seminars-24-25/#zhil
 ong_weng
ATTACH:https://warwick.ac.uk/fac/cross_fac/tia/seminars/seminars-24-25/#z
 hilong_weng
CATEGORIES:Applied Computing
LAST-MODIFIED:20250123T092447Z
ORGANIZER;CN=Adam Shephard:
END:VEVENT
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