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Rani Oomman Panicker, PhD
Rani Oomman Panicker, PhD
Manipal Institute Of Technology, Manipal Academy of Higher Education, Karnataka
Verified email at manipal.edu
Title
Cited by
Cited by
Year
Automatic detection of tuberculosis bacilli from microscopic sputum smear images using deep learning methods
RO Panicker, KS Kalmady, J Rajan, MK Sabu
Biocybernetics and Biomedical Engineering 38 (3), 691-699, 2018
1232018
A review of automatic methods based on image processing techniques for tuberculosis detection from microscopic sputum smear images
RO Panicker, B Soman, G Saini, J Rajan
Journal of medical systems 40, 1-13, 2016
762016
An adoption model describing clinician’s acceptance of automated diagnostic system for tuberculosis
RO Panicker, B Soman, KV Gangadharan, NV Sobhana
Health and Technology 6, 247-257, 2016
122016
A comparative study of different auto-focus methods for mycobacterium tuberculosis detection from brightfield microscopic images
G Saini, RO Panicker, B Soman, J Rajan
2016 IEEE Distributed Computing, VLSI, Electrical Circuits and Robotics …, 2016
112016
Factors influencing the adoption of computerized medical diagnosing system for tuberculosis
RO Panicker, MK Sabu
International Journal of Information Technology 12 (2), 503-512, 2020
72020
Automatic Detection of Tuberculosis bacilli from Conventional Sputum Smear Microscopic Images Using Densely Connected Convolutional Networks
RO Panicker, MK Sabu
SN Computer Science 3 (4), 263, 2022
52022
A lightweight convolutional neural network model for tuberculosis bacilli detection from microscopic sputum smear images
RO Panicker, SJ Pawan, J Rajan, MK Sabu
Machine learning for healthcare applications, 343-351, 2021
52021
Tuberculosis detection from conventional sputum smear microscopic images using machine learning techniques
RO Panicker, B Soman, MK Sabu
Hybrid Computational Intelligence, 63-80, 2019
32019
Adoption of Automated Clinical Decision Support System: A Recent Literature Review and a Case Study
RO Panicker, AE George
Archives of Medicine and Health Sciences 11 (1), 86-95, 2023
2023
Deep neural network based approaches for detecting tuberculosis bacilli from sputum smear microscopic images
RO Panicker
Cochin, 0
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