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CATEGORIES:Lectures & Presentations,Seminar/Colloquia
DESCRIPTION:Optical Imaging Techniques and Machine-Learning Models for Diag
 nosis of Breast\, Ovarian\, and Endometrial Cancers\n\nThis talk will focus
  on our recent progress in cancer imaging across three major research areas
 :\nUltrasound-guided diffuse optical imaging combined with machine learning
  models to improve the accurate diagnosis of breast cancer and reduce unnec
 essary breast biopsies\;\nDual-modality photoacoustic and ultrasound imagin
 g with machine learning models for accurate diagnosis of ovarian cancer and
  reduction of unnecessary surgeries\;\nOptical coherence tomography (OCT) i
 ntegrated with machine learning models for potential endometrial cancer scr
 eening and accurate diagnosis.\n\nIn our first study on ultrasound-guided d
 iffuse optical imaging\, we completed a 5-year clinical trial involving 300
  patients. The results showed a 25% reduction in unnecessary benign biopsie
 s. A fusion machine learning model demonstrated its potential to enhance ra
 diologists’ performance in further reducing these unnecessary procedures.  
 In our second study on dual-modality photoacoustic and ultrasound imaging\,
  recent diagnostic and machine learning results from over 70 patients demon
 strated significantly improved sensitivity and specificity in ovarian lesio
 n diagnosis.  In the third study\, we demonstrated that optical coherence t
 omography (OCT)\, combined with machine learning algorithms\, can be used a
 s a screening and diagnostic tool for endometrial cancer.\nFinally\, I will
  highlight our next steps toward advancing these technologies and AI tools 
 to support robust clinical translation.
DTEND:20251003T143000Z
DTSTAMP:20260414T063149Z
DTSTART:20251003T133000Z
GEO:38.648794;-90.30145
LOCATION:Preston M. Green Hall\, Rodin Auditorium room 0120
SEQUENCE:0
SUMMARY:Imaging Science & Engineering Seminar | Quing Zhu
UID:tag:localist.com\,2008:EventInstance_50789368464891
URL:https://happenings.washu.edu/event/imaging-science-engineering-seminar-
 quing-zhu
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