MISAHUB stands for Medical Imaging and Signal Analysis Hub. A virtual and open-source platform which aimed to:
- Showcase the research work done by a team of talented research students, faculty members, and healthcare professionals.
- Provide opportunities to new students, healthcare professionals, and industry collaborators to work in the field of artificial intelligence in healthcare.
The team was led by Dr. Palak Handa from the Research Center for Medical Image Analysis and AI, Department of Medicine, Danube Private University, Austria and Prof. Nidhi Goel from the Department of Electronics and Communication Engineering, Indira Gandhi Delhi Technical University for Women, Delhi, India from 2019 to 2024. The team worked on the concept of a 'mentor-mentee' wherein the mentor and mentee were selected through a rigorous process of shortlisting, evaluation, and interview. The team no longer take new mentees nor mentors. Only previous projects are in process of being completed and will be completed by 2025. Misahub's website is sponsored by DST-SERB funded project (CRG/2022/001755) and is live from 2022 to 2026 with the mission to open-source biomedical datasets for artificial intelligence in healthcare. Datasets released by the team include:
Dataset Released:
1. WCEbleedGen: A wireless capsule endoscopy dataset containing bleeding and non-bleeding frames (V1, V2)
Link to view: WCEbleedGen: A wireless capsule endoscopy dataset containing bleeding and non-bleeding frames (zenodo.org)
2. AutoWCEBleedGen-Test Dataset (V1)
Link to view: AutoWCEBleedGen-Test Dataset (zenodo.org)
For citation:
@article{hub2024auto,
title={Auto-WCEBleedGen Version V1 and V2: Challenge, Datasets and Evaluation},
author={Handa, Palak and Nautiyal, Divyansh and Chhabra, Deepti and Dhir, Manas and Saini, Anushka and Jha, Shreshtha and Mangotra, Harshita and Pandey, Nishu and Thakur, Advika and others}, journal={Authorea Preprints}, year={2024}, publisher={Authorea}} Link
3. VCEAnomalyNet
Link to view: VCE-AnomalyNet Dataset (zenodo.org)
For citation:
@article{thakur2024vce,
title={VCE-AnomalyNet: A New Dataset Fueling AI Precision in Anomaly Detection for Video Capsule Endoscopy⋆},
author={Thakur, Advika and Handa, Palak and Goel, Nidhi and Gunjan, Deepak}, journal={Authorea Preprints}, year={2024}, publisher={Authorea}}
4. AI-KODA Dataset
Citation: @article{Handa2024, author = "Ms. Palak Handa and Dr. Deepak Gunjan and Prof. Nidhi Goel and Prof. S. Indu",
title = "{AI-KODA Dataset: An AI-Image Dataset for Automatic Assessment of Cleanliness in Video Capsule Endoscopy as per Korea-Canada Scores}",
year = "2024", month = "5", url = "https://figshare.com/articles/dataset/AI-KODA_Dataset_An_AI-Image_Dataset_for_Automatic_Assessment_of_Cleanliness_in_Video_Capsule_Endoscopy_as_per_Korea-Canada_Scores/25807915", doi = "10.6084/m9.figshare.25807915.v1"}
Dataset Released
Gastrolab-Polyp test dataset
Link to view: Meta-data of published work titled 'Effect of selection bias on Automatic Colonoscopy Polyp Detection' (zenodo.org)
Gastrointestinal atlas-Colon Polyp dataset (test dataset)
Dataset Released:
1. Meta-EEG of CHB-MIT Scalp EEG Database v1.0.0.0
Link to view: https://zenodo.org/record/6062372#.ZEp6jXZBzIU
2. Meta-EEG of Siena Scalp EEG Database v1.0.0
Link to view: https://zenodo.org/record/6061290#.ZEp6i3ZBzIW
3. Dataset of rhythmicity spectrogram based images of seizure and non-seizure EEG signals
Link to view: https://zenodo.org/record/6055011#.ZEp6i3ZBzIX
For more research and internship updates:
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