Sharif Amit Kamran

Sharif Amit Kamran
  • Doctor of Philosophy
  • Post-doctoroal Scientist at Johnson & Johnson

Working on deep representation learning techniques in radiology.

About

96
Publications
15,227
Reads
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1,425
Citations
Introduction
My research interest lies in the intersection of Computer Vision, Deep Learning, and Medical Image Processing. Most of my research involves Supervised and Unsupervised algorithms for Image Classification, Semantic Segmentation, etc. Quite recently, I have been working on improving robustness, image synthesis, and image denoising using GAN on different modalities of Ophthalmological and Calcium imaging data. Website: https://sharifamit.com/
Current institution
Johnson & Johnson
Current position
  • Post-doctoroal Scientist
Additional affiliations
May 2022 - August 2022
Genentech
Position
  • Intern - Data, Analytics and Imaging
May 2021 - December 2021
Genentech
Position
  • Intern - Personalized Healthcare Imaging
August 2019 - present
University of Nevada, Reno
Position
  • Research Assistant
Education
August 2019 - December 2020
University of Nevada, Reno
Field of study
  • Computer Science & Engineering
August 2019 - May 2023
University of Nevada, Reno
Field of study
  • Computer Science and Engineering
January 2013 - April 2017
BRAC University
Field of study
  • Computer Science & Engineering

Publications

Publications (96)
Conference Paper
Semantic Segmentation using deep convolutional neural network pose more complex challenge for any GPU intensive task. As it has to compute million of parameters, it results to huge memory consumption. Moreover, extracting finer features and conducting supervised training tends to increase the complexity. With the introduction of Fully Convolutional...
Conference Paper
Diagnosing different retinal diseases from Spectral Domain Optical Coherence Tomography (SD-OCT) images is a challenging task. Different automated approaches such as image processing, machine learning and deep learning algorithms have been used for early detection and diagnosis of retinal diseases.Unfortunately, these are prone to error and computa...
Chapter
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. Due to successive resolution loss in the encoding phase combined with the inability to recover this lost information in the decoding phase, autoencoding based segmentati...
Article
Full-text available
Fluorescein angiography (FA) is a procedure used to image the vascular structure of the retina and requires the insertion of an exogenous dye with potential adverse side effects. Currently, there is only one alternative non-invasive system based on Optical coherence tomography (OCT) technology, called OCT angiography (OCTA), capable of visualizing...
Preprint
Full-text available
Psoriasis is a chronic skin condition that requires long-term treatment and monitoring. Although, the Psoriasis Area and Severity Index (PASI) is utilized as a standard measurement to assess psoriasis severity in clinical trials, it has many drawbacks such as (1) patient burden for in-person clinic visits for assessment of psoriasis, (2) time requi...
Chapter
Full-text available
The spaceflight environment introduces unique and diverse changes to the ophthalmic system. The neuro-ophthalmic phenomenon, spaceflight-associated neuro-ocular syndrome (SANS), has been identified as one of the largest physiologic barriers to future crewed long-duration spaceflight. Although one of the largest barriers, the underlying pathogenesis...
Article
Full-text available
Multiple Sclerosis (MS) is a chronic autoimmune demyelinating disease of the central nervous system (CNS) characterized by inflammation, demyelination, and axonal damage. Early recognition and treatment are important for preventing or minimizing the long-term effects of the disease. Current gold standard modalities of diagnosis (e.g., CSF and MRI)...
Article
Full-text available
Generative AI has revolutionized medicine over the past several years. A generative adversarial network (GAN) is a deep learning framework that has become a powerful technique in medicine, particularly in ophthalmology and image analysis. In this paper we review the current ophthalmic literature involving GANs, and highlight key contributions in th...
Article
Full-text available
Lower Body Negative Pressure (LBNP) redistributes blood from the upper body to the lower body. LBNP may prove to be a countermeasure for the multifaceted physiological changes endured by astronauts during spaceflight related to cephalad fluid shift. Over more than five decades, beginning with the era of Skylab, advancements in LBNP technology have...
Article
Full-text available
Spaceflight associated neuro-ocular syndrome (SANS) is one of the largest physiologic barriers to spaceflight and requires evaluation and mitigation for future planetary missions. As the spaceflight environment is a clinically limited environment, the purpose of this research is to provide automated, early detection and prognosis of SANS with a mac...
Conference Paper
Full-text available
Introduction During interplanetary spaceflight, brief periods of extreme gravitational transition are anticipated to occur between hypogravity, microgravity and hypergravity. These G-transition events may affect astronaut mission performance including dynamic visual acuity and gaze control.1,2 Significant impairments in dynamic visual acuity (DVA)...
Article
Full-text available
Empty space myopia is a phenomenon that has been observed in pilots when flying in the open sky. Previous research has been conducted to develop training biofeedback devices to help pilot visual accommodation in empty skies. During future long-duration spaceflight, astronauts may also experience empty space myopia due to prolonged periods of time i...
Article
Full-text available
Purpose To provide automated system for synthesizing fluorescein angiography (FA) images from color fundus (CF) photographs for averting risks associated with fluorescein dye and extend its future application to Space-associated neuro-ocular syndrome (SANS) detection in spaceflight where resources are limited. Design Development and validation of a...
Article
Full-text available
Purpose As the average duration of space missions increases, astronauts will experience longer periods of exposure to risks of long duration space flight including microgravity and radiation. The risks from long-term exposure to space radiation remains ill-defined. We review the current literature on the possible and known risks of radiation on the...
Article
Full-text available
Virtual reality (VR) and augmented reality (AR) are rapidly developing technologies that may have important healthcare-related applications, including the possible evaluation of the health and performance of astronauts. Advances in the fields of VR/AR and space exploration have independently progressed; however, over the last decade synergies and o...
Article
Full-text available
AI is just beginning to be integrated into clinical medicine, and will continue to be integrated into clinical care. ChatGPT has already been used in ophthalmology to triage symptoms, write operative notes, answer ophthalmic board-exam level questions and for medical education. GPT-4 builds upon the abilities of the prior GPT models by delivering m...
Article
Full-text available
Ophthalmic biomarkers have long played a critical role in diagnosing and managing ocular diseases. Oculomics has emerged as a field that utilizes ocular imaging biomarkers to provide insights into systemic diseases. Advances in diagnostic and imaging technologies including electroretinography, optical coherence tomography (OCT), confocal scanning l...
Chapter
The rapid accessibility of portable and affordable retinal imaging devices has made early differential diagnosis easier. For example, color funduscopy imaging is readily available in remote villages, which can help to identify diseases like age-related macular degeneration (AMD), glaucoma, or pathological myopia (PM). On the other hand, astronauts...
Article
Full-text available
Pendant drops of oxide-coated high-surface tension fluids frequently produce perturbed shapes that impede interfacial studies. Eutectic gallium indium (eGaIn) or gallium indium tin (Galinstan) are high-surface tension fluids coated with a ~5nm gallium oxide (Ga2O3) film and falls under this fluid classification, also known as liquid metals (LM). Th...
Article
Full-text available
Head-mounted extended reality (XR) has emerged as a powerful tool in medical education for simulation of clinical and surgical situations. Another potentially powerful clinical tool of XR may be to help clinicians further understand disease from the patient’s perception. In our work to develop a training tool for astronauts undergoing interplanetar...
Article
Spaceflight-associated neuro-ocular syndrome (SANS) is a collection of neuro-ophthalmic findings that occurs in astronauts as a result of prolonged microgravity exposure in space. Due to limited resources on board long-term spaceflight missions, early disease diagnosis and prognosis of SANS become unviable. Moreover, the current retinal imaging tec...
Article
Full-text available
An impairment in dynamic visual acuity (DVA) has been observed in astronauts shortly after they return to Earth.1 These transitional effects may lead to safety risks during interplanetary spaceflight. At this time, functional vision assessments are performed via laptop onboard the International Space Station. However, DVA is not performed as a stan...
Preprint
Full-text available
The rapid accessibility of portable and affordable retinal imaging devices has made early differential diagnosis easier. For example, color funduscopy imaging is readily available in remote villages, which can help to identify diseases like age-related macular degeneration (AMD), glaucoma, or pathological myopia (PM). On the other hand, astronauts...
Article
Full-text available
Spaceflight associated neuro-ocular syndrome (SANS) is a unique neuro-ophthalmic phenomenon that has been observed in astronauts who have undergone long-duration spaceflight. The syndrome is characterized by distinct imaging and clinical findings including optic disc edema, hyperopic refractive shift, posterior globe flattening, and choroidal folds...
Article
Full-text available
Spaceflight associated neuro-ocular syndrome (SANS) is a unique phenomenon that has been observed in astronauts who have undergone long-duration spaceflight (LDSF). The syndrome is characterized by distinct imaging and clinical findings including optic disc edema, hyperopic refractive shift, posterior globe flattening, and choroidal folds. SANS ser...
Article
Full-text available
The advent of artificial intelligence (AI) and machine learning (ML) has revolutionized the field of medicine. Although highly effective, the rapid expansion of this technology has created some anticipated and unanticipated bioethical considerations. With these powerful applications, there is a necessity for framework regulations to ensure equitabl...
Article
Full-text available
Spaceflight associated neuro-ocular syndrome (SANS) is one of the potential barriers to human long-duration spaceflight (LDSF), including a manned mission to Mars. While a large barrier, the pathophysiology of SANS is not well understood, and functional and structural findings from SANS continue to be further characterized. Currently on the Interna...
Article
Full-text available
The National Aeronautics and Space Administration (NASA) has rigorously documented a group of neuro-ophthalmic findings in astronauts during and after long-duration spaceflight known as spaceflight associated neuro-ocular syndrome (SANS). For astronaut safety and mission effectiveness, understanding SANS and countermeasure development are of utmost...
Article
Full-text available
In anticipation of space exploration where astronauts are traveling away from Earth, and for longer durations with an increasing communication lag, artificial intelligence (AI) frameworks such as large language learning models (LLMs) that can be trained on Earth can provide real-time answers. This emerging technology may be helpful for acute medica...
Article
Full-text available
Operative notes are an essential piece of documentation made by an ophthalmic team following ocular or ophthalmic surgery. While the advanced language processing capabilities of GPT-4 can be utilized to enhance the comprehension of natural language in healthcare applications, the utilization of GPT-4 in writing operative notes is not explicitly ref...
Conference Paper
Full-text available
Purpose : The aim of this study was to examine astronaut retinal nerve fiber layer (RNFL) changes with optical coherence tomography (OCT).
Article
Full-text available
GPT-4 is the latest version of ChatGPT which is reported by OpenAI to have greater problem-solving abilities and an even broader knowledge base. We examined GPT-4’s ability to inform us about the latest literature in a given area, and to write a discharge summary for a patient following an uncomplicated surgery and its latest image analysis feature...
Article
Full-text available
Purpose To evaluate the impacts of the COVID-19 on neuro-ophthalmology practice in the United States. Design Cross-sectional study. Methods The North American Neuro-ophthalmology Society distributed a survey on the impact of COVID-19 on neuro-ophthalmic practice to its members. The survey consisted of 15 questions regarding the impact of the pand...
Article
Full-text available
Brief periods of extreme gravitational transition are anticipated during interplanetary spaceflight, including transitions between microgravity, hypogravity, and hypergravity. Rapid sensorimotor adaptation will occur following these G-transitions which may affect astronaut performance including gaze control and dynamic visual acuity. Significant de...
Preprint
Full-text available
Accurately segmenting fluid in 3D volumetric optical coherence tomography (OCT) images is a crucial yet challenging task for detecting eye diseases. Traditional autoencoding-based segmentation approaches have limitations in extracting fluid regions due to successive resolution loss in the encoding phase and the inability to recover lost information...
Article
Full-text available
Background: Anecdotally, the COVID-19 pandemic has resulted in more severe cases of eye disease, decreased medication compliance/availability, and decreased treatment volume due to the lockdown. Aims: We aim to quantify and bring together a variety of international perspectives from ophthalmologists of different subspecialties to characterize th...
Article
The advent of artificial intelligence (AI) has a promising role in the future long-duration spaceflight missions. Traditional AI algorithms rely on training and testing data from the same domain. However, astronaut medical data is naturally limited to a small sample size and often difficult to collect, leading to extremely limited datasets. This si...
Article
Full-text available
Astronauts are exposed to an austere and constantly changing environment during space travel. To respond to these rapid environmental changes, high levels of dynamic visual acuity (DVA) are required. DVA is the ability to visualize objects that are in motion, or with head movement and has previously been shown to decrease significantly following sp...
Article
Full-text available
International Journal of Aviation, Aeronautics, and Aerospace, 9 (4). During interplanetary spaceflight, periods of extreme gravitational transitions will occur such as transitions between hypergravity, hypogravity, and microgravity. Following gravitational transitions, rapid sensorimotor adaptation or maladaptation may occur which can affect gaz...
Chapter
Sport-related concussion (SRC) depends on sensory information from visual, vestibular, and somatosensory systems. At the same time, the current clinical administration of Vestibular/Ocular Motor Screening (VOMS) is subjective and deviates among administrators. Therefore, for the assessment and management of concussion detection, standardization is...
Article
Full-text available
Cellular calcium fluorescence imaging utilized to study cellular behaviors typically results in large datasets and a profound need for standardized and accurate analysis methods. Here, we describe open-source software (4SM) to overcome these limitations using an automated machine learning pipeline for subcellular calcium signal segmentation of spat...
Preprint
Full-text available
Incorporating various mass shapes and sizes in training deep learning architectures has made breast mass segmentation challenging. Moreover, manual segmentation of masses of irregular shapes is time-consuming and error-prone. Though Deep Neural Network has shown outstanding performance in breast mass segmentation, it fails in segmenting micro-masse...
Article
Full-text available
INTRODUCTION: Dynamic visual acuity (DVA) refers to the ability of the eye to discern detail in a moving object and plays an important role whenever rapid physical responses to environmental changes are required, such as while performing tasks onboard a space shuttle. A significant decrease in DVA has previously been noted after astronauts returned...
Article
Full-text available
The human body undergoes many changes during long-duration spaceflight including musculoskeletal, visual, and behavioral changes. Several of these microgravity-induced effects serve as potential barriers to future exploration missions. The advent of artificial intelligence (AI) in medicine has progressed rapidly and has many promising applications...
Preprint
Full-text available
Sport-related concussion (SRC) depends on sensory information from visual, vestibular, and somatosensory systems. At the same time, the current clinical administration of Vestibular/Ocular Motor Screening (VOMS) is subjective and deviates among administrators. Therefore, for the assessment and management of concussion detection, standardization is...
Article
Full-text available
During long-duration spaceflight, astronauts are exposed to various risks including spaceflight-associated neuro-ocular syndrome, which serves as a risk to astronaut vision and a potential physiological barrier to future spaceflight. When considering exploration missions that may expose astronauts to longer periods of microgravity, radiation exposu...
Chapter
Full-text available
Automating arrhythmia detection from ECG requires a robust and trusted system that retains high accuracy under electrical disturbances. Many machine learning approaches have reached human-level performance in classifying arrhythmia from ECGs. However, these architectures are vulnerable to adversarial attacks, which can misclassify ECG signals by de...
Chapter
Full-text available
Ophthalmic images may contain identical-looking pathologies that can cause failure in automated techniques to distinguish different retinal degenerative diseases. Additionally, reliance on large annotated datasets and lack of knowledge distillation can restrict ML-based clinical support systems’ deployment in real-world environments. To improve the...
Conference Paper
Full-text available
Introduction Since the early Shuttle missions, astronauts have reported visual acuity (VA) changes that have led to anecdotes of diminished focus and reading checklists.1 Further investigation has led to the discovery of Spaceflight Associated Neuro-Ocular Syndrome (SANS), a distinct set of neuro-ophthalmic findings following long-duration spacefli...
Article
Full-text available
The neuro-ocular effects of long-duration spaceflight have been termed Spaceflight Associated Neuro-Ocular Syndrome (SANS) and are a potential challenge for future, human space exploration. The underlying pathogenesis of SANS remains ill-defined, but several emerging translational applications of terrestrial head-mounted, visual assessment technolo...
Chapter
During long-duration spaceflights, some astronauts exhibit ocular structural and functional changes called SANS. Monitoring for SANS is challenging due to time and payload constraints that limit which tests can be performed and at what frequency. A virtual reality (VR)-based system that monitors relevant aspects of ocular properties through multimo...
Preprint
Full-text available
Ophthalmic images may contain identical-looking pathologies that can cause failure in automated techniques to distinguish different retinal degenerative diseases. Additionally, reliance on large annotated datasets and lack of knowledge distillation can restrict ML-based clinical support systems' deployment in real-world environments. To improve the...
Article
Full-text available
During spaceflight, astronauts can experience significantly higher levels of hemolysis. With future space missions exposing astronauts to longer periods of microgravity, such as missions to Mars, there will be a need to for better understanding this phenomenon. We have proposed that retinal fundus photography and deep learning may be utilized to he...
Article
Full-text available
Cellular imaging instrumentation advancements as well as readily available optogenetic and fluorescence sensors have yielded a profound need for fast, accurate, and standardized analysis. Deep-learning architectures have revolutionized the field of biomedical image analysis and have achieved state-of-the-art accuracy. Despite these advancements, de...
Article
Spaceflight associated neuro-ocular syndrome (SANS) refers to a unique collection of neuro-ophthalmic clinical and imaging findings observed in astronauts after long duration spaceflight. Current in-flight and post-flight imaging modalities (e.g., optical coherence tomography, orbital ultrasound, and funduscopy) have played an instrumental role in...
Article
Full-text available
Spaceflight Associated Neuro-Ocular Syndrome (SANS) refers to a unique collection of neuro-ophthalmic clinical and imaging findings that are observed in astronauts during long duration spaceflight. These findings include optic disc edema, posterior globe flattening, retinal nerve layer fiber thickening, optic nerve sheath distension, and hyperopic...
Article
Full-text available
Certain ocular imaging procedures such as fluoresceine angiography (FA) are invasive with potential for adverse side effects, while others such as funduscopy are non-invasive and safe for the patient. However, effective diagnosis of ophthalmic conditions requires multiple modalities of data and a potential need for invasive procedures. In this stud...
Preprint
Full-text available
Recently deep learning has reached human-level performance in classifying arrhythmia from Electrocardiogram (ECG). However, deep neural networks (DNN) are vulnerable to adversarial attacks, which can misclassify ECG signals by decreasing the model's precision. Adversarial attacks are crafted perturbations injected in data that manifest the conventi...
Preprint
Full-text available
Spear Phishing is a type of cyber-attack where the attacker sends hyperlinks through email on well-researched targets. The objective is to obtain sensitive information such as name, credentials, credit card numbers, or other crucial data by imitating oneself as a trustworthy website. According to a recent report, phishing incidents nearly doubled i...
Preprint
Full-text available
Electrocardiogram (ECG) acquisition requires an automated system and analysis pipeline for understanding specific rhythm irregularities. Deep neural networks have become a popular technique for tracing ECG signals, outperforming human experts. Despite this, convolutional neural networks are susceptible to adversarial examples that can misclassify E...
Preprint
Full-text available
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 nausea, vomiting, anaphylactic shock, and even death. In contrast, color fundus imaging is a non-invasive technique used for photographing the retina but does not have s...
Preprint
Full-text available
Retinal vessel segmentation contributes significantly to the domain of retinal image analysis for the diagnosis of vision-threatening diseases. With existing techniques the generated segmentation result deteriorates when thresholded with higher confidence value. To alleviate from this, we propose RVGAN, a new multi-scale generative architecture for...
Chapter
Spectral Domain Optical Coherence Tomography (SD-OCT) is a demanding imaging technique by which diagnosticians detect retinal diseases. Automating the procedure for early detection and diagnosis of retinal diseases has been proposed in many intricate ways through the use of image processing, machine learning, and deep learning algorithms. Unfortuna...
Chapter
Full-text available
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 patient. Angiography requires insertion of a dye that may cause severe adverse effects and can even be fatal. Currently, there are no non-invasive systems capable of generati...
Preprint
Full-text available
Fluorescein Angiography (FA) is a technique that employs the designated camera for Fundus photography incorporating excitation and barrier filters. FA also requires fluorescein dye that is injected intravenously, which might cause adverse effects ranging from nausea, vomiting to even fatal anaphylaxis. Currently, no other fast and non-invasive tech...
Article
Full-text available
High-resolution Ca²⁺ imaging to study cellular Ca²⁺ behaviors has led to the creation of large datasets with a profound need for standardized and accurate analysis. To analyze these datasets, spatio-temporal maps (STMaps) that allow for 2D visualization of Ca²⁺ signals as a function of time and space are often used. Methods of STMap analysis rely o...
Preprint
Full-text available
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 retinal diseases. In addition, the lack of knowledge transferability and the need for unreasonably large datasets limit clinical application of current machine learning sy...
Preprint
Full-text available
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 patient. Angiography requires insertion of a dye that may cause severe adverse effects and can even be fatal. Currently, there are no non-invasive systems capable of generati...
Preprint
Full-text available
Diagnosing different retinal diseases from Spectral Domain Optical Coherence Tomography (SD-OCT) images is a challenging task. Different automated approaches such as image processing, machine learning and deep learning algorithms have been used for early detection and diagnosis of retinal diseases. Unfortunately, these are prone to error and comput...
Preprint
Full-text available
Diagnosing different retinal diseases from Spectral Domain Optical Coherence Tomography (SD-OCT) images is a challenging task. Different automated approaches such as image processing, machine learning and deep learning algorithms have been used for early detection and diagnosis of retinal diseases. Unfortunately, these are prone to error and comput...
Preprint
Full-text available
Solving problems with Artificial intelligence in a competitive manner has long been absent in Bangladesh and Bengali-speaking community. On the other hand, there has not been a well structured database for Bengali Handwritten digits for mass public use. To bring out the best minds working in machine learning and use their expertise to create a mode...
Preprint
Full-text available
Recognizing Traffic Signs using intelligent systems can drastically reduce the number of accidents happening world-wide. With the arrival of Self-driving cars it has become a staple challenge to solve the automatic recognition of Traffic and Hand-held signs in the major streets. Various machine learning techniques like Random Forest, SVM as well as...
Preprint
Full-text available
Recognizing Traffic Signs using intelligent systems can drastically reduce the number of accidents happening worldwide. With the arrival of Self-driving cars it has become a staple challenge to solve the automatic recognition of Traffic and Hand-held signs in the major streets. Various machine learning techniques like Random Forest, SVM as well as...
Preprint
Full-text available
Semantic Segmentation using deep convolutional neural network pose more complex challenge for any GPU intensive task. As it has to compute million of parameters, it results to huge memory consumption. Moreover, extracting finer features and conducting supervised training tends to increase the complexity. With the introduction of Fully Convolutional...

Questions

Question (1)
Question
I'm working on a GAN with multiple scaled images that will be used for Generators and Discriminators. Is Lanczos better than Bicubic for downsampling the images for training in this kind of GAN setting ?

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