Structure tensor based automated detection of macular edema and central serous retinopathy using optical coherence tomography images

Hassan, Bilal; Raja, Gulistan; Hassan, Taimur; Akram, M. Usman

doi:10.1364/josaa.33.000455

Cited by 74 publications

(40 citation statements)

References 12 publications

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“…Hassan et al [75] employed a Support Vector Machine (SVM) classifier based on five distinct features (three based on the thickness profiles of the sub-retinal layers and two based on cyst fluids within the sub-retinal layers).…”

Section: Srd Detectionmentioning

confidence: 99%

Automatic macular edema identification and characterization using OCT images

Samagaio

Estévez

Moura

et al. 2018

Computer Methods and Programs in Biomedicine

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A Tomografia de Coerência Óptica (TCO) consiste numa técnica de imagem médica não invasiva e ausente do contacto directo com o paciente que avalia in vivo a histopatologia do tecido. Esta tem sido amplamente utilizada no diagnóstico médico para identificar diversas patologias, não só associadas ao órgão em estudo no presente projecto, mas também a outras doenças em geral.A Retinopatia Diabética (RD) e a Degeneração Macular Relacionada à Idade (DMRI) são atualmente consideradas como duas das principais doenças oculares relacionadas com a perda de visão nos países desenvolvidos. Estas doenças têm em comum o acúmulo de líquido dentro do tecido retiniano, formando o Edema Macular (EM). A detecção e caracterização da acumulação de líquido intra-retiniano na mácula constitui uma questão oftalmológica crucial, dado que este fornece informações úteis na identificação e no diagnóstico dos diferentes tipos de EM, indicando consequentemente a gravidade da doença. Estes tipos de edemas da retina são clinicamente definidos, segundo a classificação de referência do campo, como: Descolamento Seroso Exsudativo da Retina (DSER), Edema Macular Difuso (EMD) e Edema Macular Cistoide (EMC).O presente trabalho visa o desenvolvimento de um sistema automático capaz de detectar e caracterizar os três tipos de EM usando imagens TCO. Este sistema de Diagnóstico Assistido por Computador (DAC) usará diferentes estratégias as quais combinam técnicas de processamento de imagem e de aprendizagem máquina com o conhecimento clínico. No caso do reconhecimento dos edemas DSER e EMC, espera-se a aplicação de abordagens com base nos diferentes limiares de intensidades característicos destes edemas, enquanto que para os EMD, dada a sua complexidade e aparência regional, deve ser aplicada uma estratégia de aprendizagem para explorar propriedades características dessa região.Esta solução permitirá assegurar a redução de custos relacionados com operações cirúrgicas e tratamento clínico aumentando assim a qualidade do diagnóstico, reduzindo a subjectividade inter-especialistas culminando na melhora da qualidade de vida do paciente. A produtividade e eficiência dos especialistas irá igualmente aumentar dado que esta solução irá o seu trabalho será facilitado. AbstractThe Optical Coherence Tomography (OCT) consists of a non-invasive and contactless medical image technique that evaluates in vivo the histopathology of the tissue. It has been widely used in medical diagnosis to identify a large range of pathologies, not only associated to the organ under the present study but also with other diseases in general.The diabetic retinopathy (DR) and the Age-related Macular Degeneration (AMD) are considered the two major eye diseases that are currently related with the vision loss in the developed countries. These diseases have in common the fluid accumulation within the retinal tissue round the macular region, forming the Macular Edema (ME). The detection and characterization of the intraretinal fluid accumulation constitutes a crucial ophthalmological issue as i...

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Section: Srd Detectionmentioning

confidence: 99%

Automatic macular edema identification and characterization using OCT images

Samagaio

Estévez

Moura

et al. 2018

Computer Methods and Programs in Biomedicine

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“…In the central region of the retina is the macula, and the fovea is near its center. This system allows detailed view [1]. Some macular pathologies are central serous retinopathy (CSR), age-related macular degeneration (AMD) and macular edema (ME) [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Automatic Segmentation of Macular Holes in Optical Coherence Tomography Images: A review

Mendes¹,

Lucena²,

Lucena³

et al. 2020

AIS

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Macular holes are a blinding condition that occur due to overuse of the fovea, in which a hole alters the natural retinal structure. Optical Coherence Tomography (OCT) is a way of mapping and shaping retinal sections without physical contact and has become a powerful tool for diagnosing pathologies. This paper deals with a review of automated segmentation of macular holes in OCT images, detailing its varied possibilities. It may be considered something new, no reviews were made about the topic. The purpose of this review is to show the latest trends, through the approaches in preprocessing and segmentation. Recent studies were used to validate the research, 2011 onwards, from the Science Direct, IEEE, PubMed and Google scholar bases. The objectives, methodology, tools, database, advantages, disadvantages, validation metrics and results of the selected material are analyzed and mentioned. Based on this, techniques and their results are compared. From this, future outlook scenarios of automated segmentation of macular holes in OCT images are mentioned.

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“…Previously, we have proposed a fully automated robust system in [24] to diagnose ME, CSR, and normal cases from 2D OCT scans and here we propose an extension of our system to incorporate automated detection and diagnoses of macular disorders. As there are different macular diseases, that is, RE, CSCR, and ARMD, which show a little bit similar variations in OCT scans near the fovea, while designing an automated system for detection of any macular disease, it is important to differentiate between these macular disorders.…”

Section: Introductionmentioning

confidence: 99%

Fully Automated Robust System to Detect Retinal Edema, Central Serous Chorioretinopathy, and Age Related Macular Degeneration from Optical Coherence Tomography Images

Khalid

Akram

Hassan

et al. 2017

BioMed Research International

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Maculopathy is the excessive damage to macula that leads to blindness. It mostly occurs due to retinal edema (RE), central serous chorioretinopathy (CSCR), or age related macular degeneration (ARMD). Optical coherence tomography (OCT) imaging is the latest eye testing technique that can detect these syndromes in early stages. Many researchers have used OCT images to detect retinal abnormalities. However, to the best of our knowledge, no research that presents a fully automated system to detect all of these macular syndromes is reported. This paper presents the world's first ever decision support system to automatically detect RE, CSCR, and ARMD retinal pathologies and healthy retina from OCT images. The automated disease diagnosis in our proposed system is based on multilayered support vector machines (SVM) classifier trained on 40 labeled OCT scans (10 healthy, 10 RE, 10 CSCR, and 10 ARMD). After training, SVM forms an accurate decision about the type of retinal pathology using 9 extracted features. We have tested our proposed system on 2819 OCT scans (1437 healthy, 640 RE, and 742 CSCR) of 502 patients from two different datasets and our proposed system correctly diagnosed 2817/2819 subjects with the accuracy, sensitivity, and specificity ratings of 99.92%, 100%, and 99.86%, respectively.

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Structure tensor based automated detection of macular edema and central serous retinopathy using optical coherence tomography images

Cited by 74 publications

References 12 publications

Automatic macular edema identification and characterization using OCT images

Automatic macular edema identification and characterization using OCT images

Automatic Segmentation of Macular Holes in Optical Coherence Tomography Images: A review

Fully Automated Robust System to Detect Retinal Edema, Central Serous Chorioretinopathy, and Age Related Macular Degeneration from Optical Coherence Tomography Images

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