Advisory Committee Chair
Leon Jololian
Advisory Committee Members
Frank M Skidmore
Despina Stavrinos
Document Type
Thesis
Date of Award
2019
Degree Name by School
Master of Science in Electrical Engineering (MSEE) School of Engineering
Abstract
This paper aims to investigate the use of unsupervised saliency proposals in extracting suitable prior information from computed tomography scans of the head using image-level labels. The weak supervision learning method obtains useful information about an object’s location and fuses this result with an unsupervised saliency proposal to propagate labels to all related pixels. However, it is shown that unsupervised saliency guidance fails to supply the synthetic annotations with enough coherence to produce suitable segmentation.
Recommended Citation
Hatcher, Solomon Lee, "The Efficacy of Weakly Supervised Learning for Biomedical Imaging" (2019). All ETDs from UAB. 1892.
https://digitalcommons.library.uab.edu/etd-collection/1892