92 citations · 354 across the 15 of their papers we have counts for
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SWIN-SFTNet : Spatial Feature Expansion and Aggregation using Swin Transformer For Whole Breast micro-mass segmentation
Sharif Amit Kamran, Khondker Fariha Hossain, Alireza Tavakkoli +2
Incorporating various mass shapes and sizes in training deep learning architectures has made breast mass segmentation challenging. Moreover, manual segmentation of masses of irregu…
Virtual-Reality based Vestibular Ocular Motor Screening for Concussion Detection using Machine-Learning
Khondker Fariha Hossain, Sharif Amit Kamran, Prithul Sarker +4
Sport-related concussion (SRC) depends on sensory information from visual, vestibular, and somatosensory systems. At the same time, the current clinical administration of Vestibula…
Feature Representation Learning for Robust Retinal Disease Detection from Optical Coherence Tomography Images
Sharif Amit Kamran, Khondker Fariha Hossain, Alireza Tavakkoli +2
Ophthalmic images may contain identical-looking pathologies that can cause failure in automated techniques to distinguish different retinal degenerative diseases. Additionally, rel…
VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers
Sharif Amit Kamran, Khondker Fariha Hossain, Alireza Tavakkoli +2
In Fluorescein Angiography (FA), an exogenous dye is injected in the bloodstream to image the vascular structure of the retina. The injected dye can cause adverse reactions such as…
RV-GAN: Segmenting Retinal Vascular Structure in Fundus Photographs using a Novel Multi-scale Generative Adversarial Network
Sharif Amit Kamran, Khondker Fariha Hossain, Alireza Tavakkoli +3
High fidelity segmentation of both macro and microvascular structure of the retina plays a pivotal role in determining degenerative retinal diseases, yet it is a difficult problem.…
Attention2AngioGAN: Synthesizing Fluorescein Angiography from Retinal Fundus Images using Generative Adversarial Networks
Sharif Amit Kamran, Khondker Fariha Hossain, Alireza Tavakkoli +1
Fluorescein Angiography (FA) is a technique that employs the designated camera for Fundus photography incorporating excitation and barrier filters. FA also requires fluorescein dye…
Improving Robustness using Joint Attention Network For Detecting Retinal Degeneration From Optical Coherence Tomography Images
Sharif Amit Kamran, Alireza Tavakkoli, Stewart Lee Zuckerbrod
Noisy data and the similarity in the ocular appearances caused by different ophthalmic pathologies pose significant challenges for an automated expert system to accurately detect r…
Fundus2Angio: A Conditional GAN Architecture for Generating Fluorescein Angiography Images from Retinal Fundus Photography
Sharif Amit Kamran, Khondker Fariha Hossain, Alireza Tavakkoli +3
Carrying out clinical diagnosis of retinal vascular degeneration using Fluorescein Angiography (FA) is a time consuming process and can pose significant adverse effects on the pati…
Optic-Net: A Novel Convolutional Neural Network for Diagnosis of Retinal Diseases from Optical Tomography Images
Sharif Amit Kamran, Sourajit Saha, Ali Shihab Sabbir +1
Diagnosing different retinal diseases from Spectral Domain Optical Coherence Tomography (SD-OCT) images is a challenging task. Different automated approaches such as image processi…