Matching Items (2)
Description
Diabetic retinopathy (DR) is a common cause of blindness occurring due to prolonged presence of diabetes. The risk of developing DR or having the disease progress is increasing over time. Despite advances in diabetes care over the years, DR remains a vision-threatening complication and one of the leading causes of blindness among American adults. Recent studies have shown that diagnosis based on digital retinal imaging has potential benefits over traditional face-to-face evaluation. Yet there is a dearth of computer-based systems that can match the level of performance achieved by ophthalmologists. This thesis takes a fresh perspective in developing a computer-based system aimed at improving diagnosis of DR images. These images are categorized into three classes according to their severity level. The proposed approach explores effective methods to classify new images and retrieve clinically-relevant images from a database with prior diagnosis information associated with them. Retrieval provides a novel way to utilize the vast knowledge in the archives of previously-diagnosed DR images and thereby improve a clinician's performance while classification can safely reduce the burden on DR screening programs and possibly achieve higher detection accuracy than human experts. To solve the three-class retrieval and classification problem, the approach uses a multi-class multiple-instance medical image retrieval framework that makes use of spectrally tuned color correlogram and steerable Gaussian filter response features. The results show better retrieval and classification performances than prior-art methods and are also observed to be of clinical and visual relevance.
ContributorsChandakkar, Parag Shridhar (Author) / Li, Baoxin (Thesis advisor) / Turaga, Pavan (Committee member) / Frakes, David (Committee member) / Arizona State University (Publisher)
Created2012
Description
Diabetic retinopathy is a disorder that affects many individuals with type 1 and type 2 diabetes mellitus. Due to increased blood glucose levels, microvessels in the retina become leaky, leading to vision loss. Through a cell culture model, this project aims to set a protocol in establishing a microvascular structure as well as investigate genetic changes that occur with the onset of diabetes. This project showcases images of microvascular-like structures which show progress into full microvascular formation as well as single cell sequencing data showing an endothelial cluster in microvascular-like structures.
ContributorsGupta, Raj (Author) / Rangasamy, Sampathkumar (Thesis director) / Legendre, Christophe (Committee member) / Barrett, The Honors College (Contributor)
Created2022-05