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MEDICAL AI
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Recent Projects
Diabetic Retinopathy
This project was to analyze scanned retinal images (eye cells like hemorrhage, vitreous hemorrhage, soft exudates, hard exudates, microaneurysms, venous beadings) for symptoms beadings) for symptoms of ocular diseases like diabetic retinopathy. The labeled data sets are used to develop an AI technology for autonomous detection of both mild and vision-threatening diabetic retinopathy. exudates, microaneurysms, venous beadings) for symptoms beadings) for symptoms of ocular diseases like diabetic retinopathy. The labeled data sets are used to develop an AI technology for autonomous detection of both mild and vision-threatening diabetic retinopathy.
Fetal Brain Labeling
In this project, brain parts (CSP, midline-falx, cranium, atrium wall, choroid plexus, sylvian fissure, brain parenchyma, cerebellar lobes, cisterna magna, Nf fluid, skin) of the fetus in ultra sonogram images were labeled.
Cerebral Angiogram Labeling
Labeled the blood vessels (CCA, ICA, ECA, MCA, ACA, vertebral, subclavian, basilar, PCA, SCA, PCOM, aorta, EIA, femoral) and surgical instruments (Catheter, Micro-Catheter, Stent, Wire) in X-Ray images. and surgical instruments (Catheter, Microcatheter, Stent, Wire) in X-Ray images.
CT Scan Labeling
In the CT scan labeling project, we labeled the vessels or arteries such as ICA, MCA, ACA, CCA, ECA, etc. There were 10 categories of vessels that needed to be labeled in CT scanned images. The images were in 3 different views, such as axial, sagittal, and coronal. There were 10 categories of vessels that needed to be labeled in CT scanned images. The images were in 3 different views, such as axial, sagittal, and coronal.
Cell Labeling
Labelers draw masks around myelinated, unmyelinated, macnuclei, and oligonuclei. oligonuclei.