Samiksha Pachade
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View article: A self-supervised learning approach for registration agnostic imaging models with 3D brain CTA
A self-supervised learning approach for registration agnostic imaging models with 3D brain CTA Open
Summary: Deep learning-based neuroimaging pipelines for acute stroke typically rely on image registration, which not only increases computation but also introduces a point of failure. In this paper, we propose a general-purpose contrastive…
View article: Author Correction: Synthetic OCT-A blood vessel maps using fundus images and generative adversarial networks
Author Correction: Synthetic OCT-A blood vessel maps using fundus images and generative adversarial networks Open
View article: Synthetic OCT-A blood vessel maps using fundus images and generative adversarial networks
Synthetic OCT-A blood vessel maps using fundus images and generative adversarial networks Open
View article: Self-Supervised Learning with Radiology Reports, A Comparative Analysis of Strategies for Large Vessel Occlusion and Brain CTA Images
Self-Supervised Learning with Radiology Reports, A Comparative Analysis of Strategies for Large Vessel Occlusion and Brain CTA Images Open
Scarcity of labels for medical images is a significant barrier for training representation learning approaches based on deep neural networks. This limitation is also present when using imaging data collected during routine clinical care st…
View article: Foveal Avascular Zone Segmentation Using Deep Learning-Driven Image-Level Optimization and Fundus Photographs
Foveal Avascular Zone Segmentation Using Deep Learning-Driven Image-Level Optimization and Fundus Photographs Open
The foveal avascular zone (FAZ) is a retinal area devoid of capillaries and associated with multiple retinal pathologies and visual acuity. Optical Coherence Tomography Angiography (OCT-A) is a very effective means of visualizing retinal v…
View article: Retinal Fundus Multi-Disease Image Dataset (RFMiD) 2.0: A Dataset of Frequently and Rarely Identified Diseases
Retinal Fundus Multi-Disease Image Dataset (RFMiD) 2.0: A Dataset of Frequently and Rarely Identified Diseases Open
Irreversible vision loss is a worldwide threat. Developing a computer-aided diagnosis system to detect retinal fundus diseases is extremely useful and serviceable to ophthalmologists. Early detection, diagnosis, and correct treatment could…
View article: Retinal Fundus Multi-Disease Image Dataset (RFMiD) 2.0
Retinal Fundus Multi-Disease Image Dataset (RFMiD) 2.0 Open
Retinal Fundus Multi-disease Image Dataset (RFMiD 2.0) is an auxiliary dataset to our previously published dataset. RFMiD 2.0 is a more challenging dataset to research society to develop the computer-based disease diagnosis system. Diabeti…
View article: Retinal Fundus Multi-Disease Image Dataset (RFMiD) 2.0
Retinal Fundus Multi-Disease Image Dataset (RFMiD) 2.0 Open
Retinal Fundus Multi-disease Image Dataset (RFMiD 2.0) is an auxiliary dataset to our previously published dataset. RFMiD 2.0 is a more challenging dataset to research society to develop the computer-based disease diagnosis system. Diabeti…
View article: Biomedical image analysis competitions: The state of current participation practice
Biomedical image analysis competitions: The state of current participation practice Open
The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known about the common practice as well as bottlenecks faced by the c…
View article: Detection of Stroke with Retinal Microvascular Density and Self-Supervised Learning Using OCT-A and Fundus Imaging
Detection of Stroke with Retinal Microvascular Density and Self-Supervised Learning Using OCT-A and Fundus Imaging Open
Acute cerebral stroke is a leading cause of disability and death, which could be reduced with a prompt diagnosis during patient transportation to the hospital. A portable retina imaging system could enable this by measuring vascular inform…
View article: UTHealth - Fundus and Synthetic OCT-A Dataset (UT-FSOCTA)
UTHealth - Fundus and Synthetic OCT-A Dataset (UT-FSOCTA) Open
Introduction Vessel segmentation in fundus images is essential in the diagnosis and prognosis of retinal diseases and the identification of image-based biomarkers. However, creating a vessel segmentation map can be a tedious and time consu…
View article: UTHealth - Fundus and Synthetic OCT-A Dataset (UT-FSOCTA)
UTHealth - Fundus and Synthetic OCT-A Dataset (UT-FSOCTA) Open
<p><strong>Introduction</strong></p>\n\n<p>Vessel segmentation in fundus images is essential in the diagnosis and prognosis of retinal diseases and the identification of image-based biomarkers. However, creati…
View article: Towards Stroke Biomarkers on Fundus Retinal Imaging: A Comparison Between Vasculature Embeddings and General Purpose Convolutional Neural Networks
Towards Stroke Biomarkers on Fundus Retinal Imaging: A Comparison Between Vasculature Embeddings and General Purpose Convolutional Neural Networks Open
Fundus Retinal imaging is an easy-to-acquire modality typically used for monitoring eye health. Current evidence indicates that the retina, and its vasculature in particular, is associated with other disease processes making it an ideal ca…
View article: Retinal Fundus Multi-Disease Image Dataset (RFMiD): A Dataset for Multi-Disease Detection Research
Retinal Fundus Multi-Disease Image Dataset (RFMiD): A Dataset for Multi-Disease Detection Research Open
The world faces difficulties in terms of eye care, including treatment, quality of prevention, vision rehabilitation services, and scarcity of trained eye care experts. Early detection and diagnosis of ocular pathologies would enable fores…
View article: IDRiD: Diabetic Retinopathy – Segmentation and Grading Challenge
IDRiD: Diabetic Retinopathy – Segmentation and Grading Challenge Open
Diabetic Retinopathy (DR) is the most common cause of avoidable vision loss, predominantly affecting the working-age population across the globe. Screening for DR, coupled with timely consultation and treatment, is a globally trusted polic…
View article: Indian Diabetic Retinopathy Image Dataset (IDRiD): A Database for Diabetic Retinopathy Screening Research
Indian Diabetic Retinopathy Image Dataset (IDRiD): A Database for Diabetic Retinopathy Screening Research Open
Diabetic Retinopathy is the most prevalent cause of avoidable vision impairment, mainly affecting the working-age population in the world. Recent research has given a better understanding of the requirement in clinical eye care practice to…