Leading-Edge Research & Publications
Research Overview
At CMIS, our research portfolio is dedicated to revolutionizing non-invasive diagnostic imaging. We leverage advanced computational techniques, including deep learning and machine vision, to extract meaningful data from complex medical scans. The primary research domains at CMIS encompass fundus imaging, ultrasonography, mammography, MRI, and CT, leveraging deep learning, computer vision, and advanced signal processing to improve early disease detection and diagnosis.
A significant milestone includes a Core Research Grant (CRG) from SERB-DST (File No. EMR/2017/000885), supporting the development of robust algorithms for detecting NVE and NVD in diabetic retinopathy. This work has yielded several high-impact publications in SCI-indexed international medical journals. Currently, CMIS is engaged in a new CRG-funded project titled “A Novel Hardware-Embedded Multivariate Feature-Enabled Health Monitoring System for Early Diagnosis of Glaucoma”, conducted in collaboration with Simadri Surya Eye Hospital, IIIT Bhubaneswar, and IIT Bhubaneswar.
Our Core Research Projects
Rural Health Care Improvement for Diabetic Retinopathy
Funding: SERB-DST (Rs. 21,73,800/-)
File Number: EMR/2017/000885
Status: Completed on 11th Sept. 2022 with GOOD grade.
Project focused on developing robust algorithms for Early Detection of NVD & NVE in Diabetic Retinopathy for rural health care improvement.
Hardware-Embedded Monitoring for Glaucoma Diagnosis
Funding: SERB-DST (Rs. 50,49,484/-)
File Number: CRG/2023/005474
Status: Ongoing
Developing a novel hardware-embedded multivariate feature-enabled health monitoring system for the early diagnosis of Glaucoma.
Our Funding Agencies
ANRF
CSIR
Recent Publications
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[1] MSFCS-Net: A Dual-Decoder Architecture for an Efficient Segmentation of Optic Disc and Optic Cup
Kowju Gayatri, Birendra Biswal, Singam Aruna . | IETE Journal of Research, Taylor & Francis (Impact Factor: 1.3, Coverage: SCIE)
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[2] A Robust Segmentation of Retinal Fluids from OCT images using MCSAR-Net
Geetha Pavani P, B Biswal, Srinivasa Rao Kandula, PK Biswal, G Siddartha, T Niranjan, Bala Subrahmanyam N, Bala Subramanyam . | Neurocomputing, Elsevier (Impact Factor: 5.687, Coverage: SCIE)
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[3] MAEU-NET: A novel supervised architecture for brain tumor segmentation
Sangeet Kumar, B Biswal | International Journal of Imaging Systems and Technology (WILEY USA) (Impact Factor: 3.3, Coverage: SCIE)
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[4] Shell-Net: A Robust Deep Neural Network for the Joint Segmentation of Retinal Fragments
P Gowri Shankar, B Biswal, et al. | International Journal of Imaging Systems and Technology (WILEY USA) (Impact Factor: 3.3, Coverage: SCIE)
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[5] Robust Semantic Segmentation of Retinal Fluids from SD-OCT images using FAM-U-Net
Geetha Pavani P, B Biswal, Tapan Kumar Gandhi, Anaji Rao | Biomedical Signal Processing and Control, Elsevier (Impact Factor: 5.1, Coverage: SCIE)
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[6] Reactive Power Compensation Using Electric Vehicle and Data Center by Integrating Virtual Power Plant
Neethu Elizabeth Michael, Shazia Hasan, B Biswal, et al. | Electric Power Components and Systems (Coverage: SCIE)
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[7] Simultaneous Multiclass Retinal Lesion Segmentation using fully automated RILBP-Y Net in Diabetic Retinopathy
B Biswal, Sreekar Tankala, Geetha Pavani P, et al. | Biomedical Signal Processing and Control (Impact Factor: 5.1, Coverage: SCIE)
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[8] EANet: Multiscale Auto encoder-based Edge Attention Network for Fluid Segmentation from SD-OCT Images
B Biswal, Sreekar Tankala, Geetha Pavani P, et al. | International Journal of Imaging Systems and Technology (Impact Factor: 3.3, Coverage: SCIE)
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[9] A novel depth search based light weight CAR network for the segmentation of brain tumour from MR images
Sreekar Tankala, Geetha Pavani, Birendra Biswal, et al. | Neuroscience Informatics
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[10] Multistage DPIRef-Net: An Effective Network for Semantic Segmentation of Arteries and Veins from Retinal Surface
Geetha Pavani P, B Biswal, Tapan Kumar Gandhi | Neuroscience Informatics
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[11] A Deeply Supervised Maximum Responsive SegNet for Simultaneous Multi Retinal Lesion Segmentation
Geetha Pavani P, Krishna T, B Biswal, et al. | International Journal of Imaging Systems and Technology (Impact Factor: 3.3, Coverage: SCIE)
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[12] An Efficient Epileptic Seizure Classification System Using Empirical Wavelet Transform...
S. K Rout, M Sahani, C Dora, P. K. Biswal, B. Biswal | Biomedical Signal Processing and Control (Impact Factor: 5.1, Coverage: SCIE)
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[13] Robust Segmentation of Vascular Network using Deeply Cascaded AReN-UNet
Aamer Abdul Rahman, B. Biswal, Geetha Pavani P, et al. | Biomedical Signal Processing and Control (Impact Factor: 5.1, Coverage: SCIE)
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[14] Robust segmentation of exudates from retinal surface using M-CapsNet Via EM Routing
B. Biswal, Geetha Pavani P, Prasanna T, Prakash Kumar Karn | Biomedical Signal Processing and Control (Impact Factor: 5.1, Coverage: SCIE)
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[15] A semantic contour-based segmentation of lungs from chest x-rays...
Geetha Pavani P, B. Biswal, M.V.S Sairam, et al. | International Journal of Imaging Systems and Technology (Impact Factor: 3.3, Coverage: SCIE)
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[16] Robust Classification of Neovascularization using Random Forest Classifier via Convoluted Vascular Network
Geetha Pavani P, B. Biswal, P. K. Biswal, et al. | Biomedical Signal Processing and Control (Impact Factor: 5.1, Coverage: SCIE)
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[17] An Exclusive Disjunction based Detection of Neovascularization using Multiscale CNN
Geetha Pavani P, B. Biswal, T.K. Gandhi, M.V.S Sairam | IET Image Processing (Impact Factor: 2.004, Coverage: SCIE)
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[18] Classification of Neovascularization on Retinal Images using Extreme Learning Machine
Geetha Pavani P, B. Biswal, T.K. Gandhi, M.V.S Sairam | International Journal of Imaging Systems and Technology (Impact Factor: 2.000, Coverage: SCIE)
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[19] Adaptive SSA Based Muscle Artifact Removal from Single-Channel EEG using Neural Network Regressor
C. Dora, R. N Patro, S.K Rout, P.K. Biswal, B Biswal | Innovation and Research in Biomedical Engineering (IRBM) Elsevier (Impact Factor: 4.9, Coverage: SCIE)
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[20] Controlled differential evolution based detection of neovascularization...
B. Biswal, Geetha Pavani P, P. K. Biswal | Biomedical Engineering/Biomedizinische Technik (Impact Factor: 1.411, Coverage: SCIE)
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[21] Robust Retinal Optic Disc and Optic Cup Segmentation Using Statistical Kurtosis Test
B. Biswal, Eadara Vyshnavi, D.K Bebarta, et al. | International Journal of Imaging Systems and Technology (Impact Factor: 3.3, Coverage: SCIE)
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[22] Robust Retinal Optic Disc and Optic Cup Segmentation via Stationary Wavelet Transform and Maximum Vessel Pixel Sum
B. Biswal, Eadara Vyshnavi, M.V.S Sairam, et al. | IET Image Processing (Impact Factor: 2.004, Coverage: SCIE)
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[23] Robust Retinal Blood Vessel Segmentation Using Hybrid Active Contour Model
Prakash Kumar Karn, B.Biswal, S. R Samantray | IET Image Processing (Impact Factor: 2.004, Coverage: SCIE)
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[24] Robust Retinal Blood Vessel Segmentation Using Line Detectors with Multiple Masks
B. Biswal, T.Pooja, N Balasubramanyam | IET Image Processing (Impact Factor: 2.004, Coverage: SCIE)
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[25] ECG Signal Analysis using Modified S-transform
B. Biswal | Health Care Technology Letters (Coverage: SCOPUS, ESCI)
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Patents & Recent Works
Patents Granted/Published
Multivariable AI-Based Monitoring System for Glaucoma
Filing: US Patent (Application No: 18/161,042)
Patent No: US20250139778A1
System for the Early Detection of Glaucoma using artificial intelligence and monitoring system integration.
View PatentAI-based Touch-Free Automation System
Filing: Indian Patent (Application No: 202541044028 A)
Status: Published
System for Controlling Household Devices using touch-free automation and artificial intelligence.
View PatentRecent Works (Highlights)
Glaucoma Monitoring System Development
This work is the practical embodiment of our US Patent, focusing on implementing the AI monitoring system for collaborative clinical testing.
View PublicationRetinal Fluid Segmentation using MCSAR-Net
A highlight of the latest publication on achieving robust segmentation of retinal fluids from OCT images, critical for tracking macular edema.
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