[Faculty] Fwd: [CSRC.COLLOQUIUM] "Machine Learning Techniques for Biomedical Image Characterization"

[Jose Castillo]

[image: SDSU_CSRC Logo.jpg]




DATE:
*Friday, October 2, 2020*



TITLE:

*Machine Learning Techniques for Biomedical Image Characterization*


TIME:
*3:00-4:00PM*




LOCATION:
Join Zoom Meeting -  *https://SDSU.zoom.us/j/91071174391*
<https://sdsu.zoom.us/j/91071174391>



SPEAKER/BIO:

*Dr. Kyle Hasenstab, Mathematics and Statistics, San Diego State
University *





ABSTRACT:


In this talk, we shall discuss machine learning techniques for the
characterization of biomedical images in MRI and CT in the context of two
clinical applications. The first clinical application investigates methods
for assessing diagnostic adequacy of liver images in MRI using traditional
machine learning and deep neural networks. Proposed algorithms are compared
across varying sample sizes to determine advantages of either approach. The
second application investigates the relationship between lung structure
using CT images and lung function using pulmonary function tests (PFTs) in
the context of COPD. Two pathophysiological imaging features extracted from
inspiratory and expiratory CT images were found to accurately predict
PFT-based COPD diagnosis, suggesting imaging-based staging can be used as a
screening tool for COPD.




Host: Barbara Bailey

Note: Videos of previous colloquium talks can be seen on the CSRC website
in the colloquium archive section or on the CSRC YouTube page here
<https://www.youtube.com/channel/UCN0ZEztlmyDqG2pm-Rle_Eg/feed>.



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