Dr. Khalil Abuosba will present A Computer-aided Diagnostic (CAD) System for Early Assessment of Renal Transplants

A COMPUTER-AIDED DIAGNOSTIC (CAD) SYSTEM FOR EARLY ASSESSMENT OF RENAL TRANSPLANTS

This presentation introduces a deep-learning based computer-aided diagnostic (CAD) system for the early detection of renal transplant rejection. The system is based on the fusion of both imaging markers and clinical biomarkers. The imaging markers are derived from diffusion-weighted magnetic resonance imaging (DW-MRI) while the clinical biomarkers used are : creatinine clearance (CrCl) and serum plasma creatinine (SPCr).

To extract these image-markers, apparent diffusion coefficients (ADCs) are estimated from the segmented DW-MRIs and cumulative distribution functions (CDFs) of the ADCs are constructed at different b-values (i.e. gradient field strengths and duration). Finally, these markers (i.e. CDFs) are integrated with the clinical biomarkers ( CrCl and SPCr) to assess transplant status using deep learning classification approach.

The system showed high diagnostic accuracy to distinguish nonrejection (NR) from dysfunctional (DF) transplants. The results hold promise of the proposed CAD system as a reliable, inexpensive, and non-invasive diagnostic tool.

Zoom link https://lakeheadu.zoom.us/j/93172465169?pwd=M0psbks3L1BLNkRhY01pSG9ucktD...
Meeting ID: 931 7246 5169
Contact Brenda Magajna at phd.ses@lakeheadu.ca for the password