BIOMISA Databases
Retinal Image Database for Macular and Glaucomatous Disorders
A comprehensive collection of retinal images focused on macular and Glaucomatous disorders.
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Age-Related Macular Degeneration(ARMD)
A comprehensive collection of age related macular degeneration images.
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Hypertensive Retinopathy
A comprehensive collection of Hypertensive Retinopathy related images.
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Glaucoma fundus and OCT Dataset
A comprehensive collection of retinal images focused Glaucoma fundus and OCT.
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Retina Identification
A comprehensive collection of Retina images for Identification.
Access Database![Retinal Image Database Thumbnail](http://biomisa.org/wp-content/uploads/2024/10/sEMG.jpg")
sEMG Database for routine activities
A comprehensive collection of sEMG images focused daily activities.
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Skin Histology (stained and unstained pairs)
A comprehensive collection of images related skin Histology (stained and unstained pairs).
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E-Staining DermaRepo
A comprehensive collection of H&E whole slide image staining dataset.
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UAV sensor failures dataset
A comprehensive collection of images related UAV’s Sensor’s Failures.
Access DatabaseOther Databases
- Diabetic Retinopathy Database DIARETDB
- MESSIDOR Digital Retinal Images MESSIDOR
- Hamilton Eye Institute Macular Edema Dataset HEI-DMED
- Digital Retinal Images for Vessel Extraction DRIVE
- Structured Analysis of the Retina STARE
- Digital Retinal Images for Optic Nerve Segmentation Database DRIONS
- High-Resolution Fundus Image Database HRF
Software
- AL-BASR 3D Retinal Visualizer
- BIOMISA Retinal Image Illustrator
- Beatannotate – A tool for annotation of Phonocardiography signals
Paper Codes
- Clinically Verified Hybrid Deep Learning System for Retinal Ganglion Cells Aware Grading of Glaucomatous Progression (IEEE TBME, Source code is available on GitHub)
- Exploiting the Transferability of Deep Learning Systems Across Multi-modal Retinal Scans for Extracting Retinopathy Lesions (IEEE BIBE-2020, Source Code)
- RAG-FW (Paper, Source Code). Password: abc123
- CXR Report Generation: Attention based Automated Radiology Report Generation using CNN and LSTM (Code)
Workshops
- Hands on Workshop on Deep Learning with Applications in HealthCare (Data)