Segmentation-based Deep Learning Fundus Image Analysis

Qian, Wu (författare): Blekinge Tekniska Högskola,Institutionen för datavetenskap

Cheddad, Abbas (författare): Blekinge Tekniska Högskola,Institutionen för datavetenskap,BigData@BTH

(creator_code:org_t)

IEEE, 2019
2019
Engelska.
Ingår i: 2019 IEEE 27TH INTERNATIONAL REQUIREMENTS ENGINEERING CONFERENCE WORKSHOPS (REW 2019). - : IEEE. - 9781728151656 ; , s. 44-53

Relaterad länk:: http://www.ipta-conf...; visa fler...; https://urn.kb.se/re...; https://doi.org/10.1...; visa färre...

Abstract Ämnesord

Stäng

Diabetic retinopathy is the most common cause of new cases of blindness in people of working age. Early diagnosis is the key to slowing the progression of the disease, thus preventing blindness. Retinal fundus images form an important basis for judging these retinal diseases. To the best of our knowledge, no prior studies have scrutinized the predictive power of the different compositions of retinal images using deep learning. This paper is to investigate whether there exists specific region that could assist in better prediction of the retinopathy disease, meaning to find the best region in fundus images that can boost the prediction power of models for retinopathy classification. To this end, with image segmentation techniques, the fundus image is divided into three different segments, namely, the optic disc, the blood vessels, and the other regions (regions other than blood vessels and optic disk). These regions are then contrasted against the performance of original fundus images. The convolutional neural network as well as transfer deep learning with the state-of-the-art pre-trained models (i.e., AlexNet, GoogleNet, Resnet50, VGG19) are deployed. We report the average of ten runs for each model. Different machine learning evaluation metrics are used. The other regions' segment reveals more predictive power than the original fundus image especially when using AlexNet/Resnet50.

TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)
ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Image Processing (hsv//eng)
TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)
TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)

Om ämnet

TEKNIK OCH TEKNOLOGIER: TEKNIK OCH TEKNO ...; och Medicinteknik; och Medicinsk bildbe ...

TEKNIK OCH TEKNOLOGIER: TEKNIK OCH TEKNO ...; och Elektroteknik oc ...; och Signalbehandling

TEKNIK OCH TEKNOLOGIER: TEKNIK OCH TEKNO ...; och Elektroteknik oc ...; och Datorsystem

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