March 29 – Doctoral Seminar: Muneera Alsaedi

Speaker: Muneera Alsaedi

Supervisors: Dr. T. Fevens, A. Krzyzak

Supervisory Committee: Drs. M. A. Amer, T. Popa, C. Y. Suen

Title: Cytological Malignancy Grading Systems for Fine Needle Aspiration Biopsies of Breast Cancer

Date: Thursday, March 29, 2018

Time: 10:15 a.m.

Place: EV 3.309

ABSTRACT

A prime factor deciding the survival rate of a breast cancer patient is the accuracy with which the malignancy grade of a breast tumor is determined. A Fine Needle Aspiration (FNA) biopsy is a key mechanism for breast cancer diagnosis as well as for assigning grades to malignant cases.

In this study, based on published cytological malignancy grading systems, we propose six computer-aided grading frameworks to assign malignancy grades to cytological images of FNA biopsies of breast cancer using a set of efficient handcrafted features that estimated to be very tightly to pathologist characteristics.

The proposed computer-aided grading frameworks were tested on 332 FNA biopsy images composed of 66 images with high malignancy (G3) and 266 images with intermediate malignancy (G2) that were histopathologically validated using the Bloom-Richardson grading system. To provide a robust indication of the performance abilities of these frameworks, we calculated different measures as well as the 95% confidence intervals, using the Student’s t-distribution.