1. Articles from Taimur Hassan

    1-6 of 6
    1. RAG-FW: A hybrid convolutional framework for the automated extraction of retinal lesions and lesion-influenced grading of human retinal pathology

      RAG-FW: A hybrid convolutional framework for the automated extraction of retinal lesions and lesion-influenced grading of human retinal pathology

      The identification of retinal lesions plays a vital role in accurately classifying and grading retinopathy. Many researchers have presented studies on optical coherence tomography (OCT) based retinal image analysis over the past. However, to the best of our knowledge, there is no framework yet available that can extract retinal lesions from multi-vendor OCT scans and utilize them for the intuitive severity grading of the human retina. To cater this lack, we propose a deep retinal analysis and grading framework (RAG-FW). RAG-FW is a hybrid convolutional framework that extracts multiple retinal lesions from OCT scans and utilizes them for lesion-influenced grading ...

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    2. RAG-FW: A hybrid convolutional framework for the automated extraction of retinal lesions and lesion-influenced grading of human retinal pathology

      RAG-FW: A hybrid convolutional framework for the automated extraction of retinal lesions and lesion-influenced grading of human retinal pathology

      Retinopathy refers to any damage in the retina that causes visual impairments or even blindness. Identification of retinal lesions plays a vital role in accurately grading retinopathy and for its effective treatment. Optical coherence tomography (OCT) imaging is the most popular non-invasive technique used for the retinal examination due to its ability to screen abnormalities in early stages. Many researchers have presented studies on OCT based retinal image analysis over the past. However, to our best knowledge, there is no framework yet available which can extract retinal lesions from multi-vendor OCT scans and utilize them for the intuitive grading of ...

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    3. Automated Segmentation and Quantification of Drusen in Fundus and Optical Coherence Tomography Images for Detection of ARMD

      Automated Segmentation and Quantification of Drusen in Fundus and Optical Coherence Tomography Images for Detection of ARMD

      Age-related macular degeneration (ARMD) is one of the most common retinal syndromes that occurs in elderly people. Different eye testing techniques such as fundus photography and optical coherence tomography (OCT) are used to clinically examine the ARMD-affected patients. Many researchers have worked on detecting ARMD from fundus images, few of them also worked on detecting ARMD from OCT images. However, there are only few systems that establish the correspondence between fundus and OCT images to give an accurate prediction of ARMD pathology. In this paper, we present fully automated decision support system that can automatically detect ARMD by establishing correspondence ...

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

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

      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 ...

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

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

      Macular edema (ME) and central serous retinopathy (CSR) are two macular diseases that affect the central vision of a person if they are left untreated. Optical coherence tomography (OCT) imaging is the latest eye examination technique that shows a cross-sectional region of the retinal layers and that can be used to detect many retinal disorders in an early stage. Many researchers have done clinical studies on ME and CSR and reported significant findings in macular OCT scans. However, this paper proposes an automated method for the classification of ME and CSR from OCT images using a support vector machine (SVM ...

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    6. Review of OCT and fundus images for detection of Macular Edema

      Review of OCT and fundus images for detection of Macular Edema

      Macula is an oval shaped area near the center of human retina that covers the area of 5500 microns and at its center, there is a small pit known as fovea with the diameter of 1500 microns. Macular disorders involve group of diseases that damages macula resulting in blindness or vision loss. Macular Edema ‘ME’ is the most common disease related to macula. The symptoms for this disease usually appear in final stages to patient when it is very difficult to cure it and at that time it causes severe damage to central vision. However if it is detected in ...

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    1-6 of 6
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    1. (6 articles) National Institutes of Health
    2. (2 articles) UC Irvine
    3. (2 articles) Oregon Health & Science University
    4. (2 articles) Zhongping Chen
    5. (2 articles) Yifan Jian
    6. (1 articles) UCLA
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    Review of OCT and fundus images for detection of Macular Edema Structure tensor based automated detection of macular edema and central serous retinopathy using optical coherence tomography images Fully Automated Robust System to Detect Retinal Edema, Central Serous Chorioretinopathy, and Age Related Macular Degeneration from Optical Coherence Tomography Images Automated Segmentation and Quantification of Drusen in Fundus and Optical Coherence Tomography Images for Detection of ARMD RAG-FW: A hybrid convolutional framework for the automated extraction of retinal lesions and lesion-influenced grading of human retinal pathology RAG-FW: A hybrid convolutional framework for the automated extraction of retinal lesions and lesion-influenced grading of human retinal pathology The Effect of Anti-Tubercular Drugs on Retinal Nerve Fiber Layer Thickness Using Optical Coherence Tomography A Cross-sectional Optical Coherence Tomography Study in Patients on Taxane-based Therapy and A Case Report with the Literature Review Association of systemic inflammatory biomarkers with morphological characteristics of the coronary atherosclerotic plaque by intravascular optical coherence tomography. OCT angiography improves views of retina blood flow Real-time retinal layer segmentation of OCT Volumes with GPU and Deep learning Baylor College of Medicine Receives a 2020 NIH Grant for Biomechanics of Early Mammalian Cardiogenesis