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2020 – today
- 2024
[j47]Rishi Raj
, Dayananda Pruthviraja, Ayush Gupta, Jimson Mathew, Santhosh Kumar Kannath, Adity Prakash, Jeny Rajan:
Multilevel Multimodal Framework for Automatic Collateral Scoring in Brain Stroke. IEEE Access 12: 33730-33748 (2024)- [j46]Siva Bonthada, Sankar Pariserum Perumal, Poornanand Purushottam Naik, Mahesh A. Padukudru, Jeny Rajan:
An automated deep learning pipeline for detecting user errors in spirometry test. Biomed. Signal Process. Control. 90: 105845 (2024) - [j45]A. S. Neethi, Santhosh Kumar Kannath, Adarsh Anil Kumar, Jimson Mathew, Jeny Rajan:
A comprehensive review and experimental comparison of deep learning methods for automated hemorrhage detection. Eng. Appl. Artif. Intell. 133: 108192 (2024) - [j44]Bhavesh Varma, Naik Nitesh Navnath, K. Chandrasekaran, M. Venkatesan, Jeny Rajan:
Forecasting Land-Use and Land-Cover Change Using Hybrid CNN-LSTM Model. IEEE Geosci. Remote. Sens. Lett. 21: 1-5 (2024) - [j43]Rajath C. Aralikatti, S. J. Pawan, Jeny Rajan:
A Dual-Stage Semi-Supervised Pre-Training Approach for Medical Image Segmentation. IEEE Trans. Artif. Intell. 5(2): 556-565 (2024) - 2023
- [j42]Mohammad Rahil, B. N. Anoop, G. N. Girish, Abhishek R. Kothari, Shashidhar G. Koolagudi, Jeny Rajan:
A Deep Ensemble Learning-Based CNN Architecture for Multiclass Retinal Fluid Segmentation in OCT Images. IEEE Access 11: 17241-17251 (2023) - [j41]Rishi Raj, Jimson Mathew, Santhosh Kumar Kannath, Jeny Rajan:
StrokeViT with AutoML for brain stroke classification. Eng. Appl. Artif. Intell. 119: 105772 (2023) - [j40]Tojo Mathew, C. I. Johnpaul, B. Ajith, Jyoti R. Kini, Jeny Rajan:
A deep learning based classifier framework for automated nuclear atypia scoring of breast carcinoma. Eng. Appl. Artif. Intell. 120: 105949 (2023) - [j39]R. C. Radha, B. S. Raghavendra, B. V. Subhash, Jeny Rajan, A. V. Narasimhadhan:
Machine learning techniques for periodontitis and dental caries detection: A narrative review. Int. J. Medical Informatics 178: 105170 (2023) - [j38]Novanto Yudistira, Muthu Subash Kavitha, Jeny Rajan, Takio Kurita:
Attention-effective multiple instance learning on weakly stem cell colony segmentation. Intell. Syst. Appl. 17: 200187 (2023) - [j37]S. J. Pawan, Rishi Sharma, Hemanth Sai Ram Reddy, M. Vani, Jeny Rajan:
WideCaps: a wide attention-based capsule network for image classification. Mach. Vis. Appl. 34(4): 52 (2023) - [c21]Sanjana J, Poornanand Purushottam Naik, Mahesh A. Padukudru, Shashidhar G. Koolagudi, Jeny Rajan:
Attention-Based CRNN Models for Identification of Respiratory Diseases from Lung Sounds. ICCCNT 2023: 1-7 - 2022
- [j36]Tojo Mathew, S. Niyas, C. I. Johnpaul, Jyoti R. Kini, Jeny Rajan:
A novel deep classifier framework for automated molecular subtyping of breast carcinoma using immunohistochemistry image analysis. Biomed. Signal Process. Control. 76: 103657 (2022) - [j35]A. S. Neethi, S. Niyas, Santhosh Kumar Kannath, Jimson Mathew, Ajimi Mol Anzar, Jeny Rajan:
Stroke classification from computed tomography scans using 3D convolutional neural network. Biomed. Signal Process. Control. 76: 103720 (2022) - [j34]Rishi Raj, Jimson Mathew, Santhosh Kumar Kannath, Jeny Rajan:
Crossover based technique for data augmentation. Comput. Methods Programs Biomed. 218: 106716 (2022) - [j33]S. Niyas, S. J. Pawan, M. Anand Kumar, Jeny Rajan:
Medical image segmentation with 3D convolutional neural networks: A survey. Neurocomputing 493: 397-413 (2022) - [j32]S. J. Pawan, Jeny Rajan:
Capsule networks for image classification: A review. Neurocomputing 509: 102-120 (2022) - [j31]Tojo Mathew, B. Ajith, Jyoti R. Kini, Jeny Rajan:
Deep learning-based automated mitosis detection in histopathology images for breast cancer grading. Int. J. Imaging Syst. Technol. 32(4): 1192-1208 (2022) - [j30]Govind Jeevan, Geevar C. Zacharias, Madhu S. Nair, Jeny Rajan:
An empirical study of the impact of masks on face recognition. Pattern Recognit. 122: 108308 (2022) - [c20]S. Niyas, Shraddha Priya, Reena Oswal, Tojo Mathew, Jyoti R. Kini, Jeny Rajan:
Automated Molecular Subtyping of Breast Cancer Through Immunohistochemistry Image Analysis. CVMI 2022: 23-35 - [c19]Dheeraj Kumar Srivastava, S. J. Pawan, Jeny Rajan:
An Automated Approach for Screening COVID-19 from Thermal Images Using Convolutional Neural Network. AIIIMA/MIABID@MICCAI 2022: 83-91 - [c18]Govind Jeevan, S. J. Pawan, Jeny Rajan:
Cross Task Temporal Consistency for Semi-supervised Medical Image Segmentation. MLMI@MICCAI 2022: 140-150 - [i4]Novanto Yudistira, Muthu Subash Kavitha, Jeny Rajan, Takio Kurita:
Attention-effective multiple instance learning on weakly stem cell colony segmentation. CoRR abs/2203.04606 (2022) - 2021
- [j29]B. N. Anoop, Kaushik S. Kalmady, Akhil Udathu, V. Siddharth, G. N. Girish, Abhishek R. Kothari, Jeny Rajan:
A cascaded convolutional neural network architecture for despeckling OCT images. Biomed. Signal Process. Control. 66: 102463 (2021) - [j28]S. Niyas, S. Chethana Vaisali, Iwrin Show, T. G. Chandrika, S. Vinayagamani, Chandrasekharan Kesavadas, Jeny Rajan:
Segmentation of focal cortical dysplasia lesions from magnetic resonance images using 3D convolutional neural networks. Biomed. Signal Process. Control. 70: 102951 (2021) - [j27]Pawan S. Jogi, Rahul Sankar, Anubhav Jain, Mahir Jain, D. V. Darshan, B. N. Anoop, Abhishek R. Kothari, M. Venkatesan, Jeny Rajan:
Capsule Network-based architectures for the segmentation of sub-retinal serous fluid in optical coherence tomography images of central serous chorioretinopathy. Medical Biol. Eng. Comput. 59(6): 1245-1259 (2021) - [j26]Edwin Thomas, Pawan S. Jogi, Shushant Kumar, Anmol Horo, S. Niyas, S. Vinayagamani, Chandrasekharan Kesavadas, Jeny Rajan:
Multi-Res-Attention UNet: A CNN Model for the Segmentation of Focal Cortical Dysplasia Lesions from Magnetic Resonance Images. IEEE J. Biomed. Health Informatics 25(5): 1724-1734 (2021) - [c17]B. N. Anoop, Saswat Parida, B. Ajith, G. N. Girish, Abhishek R. Kothari, Muthu Subash Kavitha, Jeny Rajan:
Attention Assisted Patch-Wise CNN for the Segmentation of Fluids from the Retinal Optical Coherence Tomography Images. PReMI 2021: 213-223 - [i3]Pawan S. Jogi, Rishi Sharma, Hemanth Sai Ram Reddy, M. Vani, Jeny Rajan:
WideCaps: A Wide Attention based Capsule Network for Image Classification. CoRR abs/2108.03627 (2021) - [i2]S. Niyas, S. J. Pawan, M. Anand Kumar, Jeny Rajan:
Medical Image Segmentation using 3D Convolutional Neural Networks: A Review. CoRR abs/2108.08467 (2021) - [i1]S. J. Pawan, Rahul Sankar, Amithash M. Prabhudev, P. A. Mahesh, K. Prakashini, Sudha Kiran Das, Jeny Rajan:
MobileCaps: A Lightweight Model for Screening and Severity Analysis of COVID-19 Chest X-Ray Images. CoRR abs/2108.08775 (2021) - 2020
- [j25]P. V. Sudeep, Palanisamy Ponnusamy, Chandrasekharan Kesavadas, Jeny Rajan:
An improved nonlocal maximum likelihood estimation method for denoising magnetic resonance images with spatially varying noise levels. Pattern Recognit. Lett. 139: 34-41 (2020) - [j24]G. N. Girish, Abhishek R. Kothari, Jeny Rajan:
Marker controlled watershed transform for intra-retinal cysts segmentation from optical coherence tomography B-scans. Pattern Recognit. Lett. 139: 86-94 (2020)
2010 – 2019
- 2019
- [j23]K. M. Bijay Dev, Pawan S. Jogi, S. Niyas, S. Vinayagamani, Chandrasekharan Kesavadas, Jeny Rajan:
Automatic detection and localization of Focal Cortical Dysplasia lesions in MRI using fully convolutional neural network. Biomed. Signal Process. Control. 52: 218-225 (2019) - [j22]Chetan L. Srinidhi, P. Aparna, Jeny Rajan:
Automated Method for Retinal Artery/Vein Separation via Graph Search Metaheuristic Approach. IEEE Trans. Image Process. 28(6): 2705-2718 (2019) - [j21]G. N. Girish, Bibhash Thakur, Sohini Roychowdhury, Abhishek R. Kothari, Jeny Rajan:
Segmentation of Intra-Retinal Cysts From Optical Coherence Tomography Images Using a Fully Convolutional Neural Network Model. IEEE J. Biomed. Health Informatics 23(1): 296-304 (2019) - [c16]T. J. Narendra Rao, G. N. Girish, Abhishek R. Kothari, Jeny Rajan:
Deep Learning Based Sub-Retinal Fluid Segmentation in Central Serous Chorioretinopathy Optical Coherence Tomography Scans. EMBC 2019: 978-981 - [c15]G. N. Girish, Banoth Saikumar, Sohini Roychowdhury, Abhishek R. Kothari, Jeny Rajan:
Depthwise Separable Convolutional Neural Network Model for Intra-Retinal Cyst Segmentation. EMBC 2019: 2027-2031 - 2018
- [j20]Wadageri Yamanappa, P. V. Sudeep, M. K. Sabu, Jeny Rajan:
Non-Local Means Image Denoising Using Shapiro-Wilk Similarity Measure. IEEE Access 6: 66914-66922 (2018) - [j19]Y. Nagaraj, Pardhu Madipalli, Jeny Rajan, P. Krishna Kumar, Adapa Venkata Narasimhadhan:
Segmentation of intima media complex from carotid ultrasound images using wind driven optimization technique. Biomed. Signal Process. Control. 40: 462-472 (2018) - [j18]Chetan L. Srinidhi, P. Aparna, Jeny Rajan:
A visual attention guided unsupervised feature learning for robust vessel delineation in retinal images. Biomed. Signal Process. Control. 44: 110-126 (2018) - [j17]G. N. Girish, V. A. Anima, Abhishek R. Kothari, P. V. Sudeep, Sohini Roychowdhury, Jeny Rajan:
A benchmark study of automated intra-retinal cyst segmentation algorithms using optical coherence tomography B-scans. Comput. Methods Programs Biomed. 153: 105-114 (2018) - [j16]P. Krishna Kumar, Tadashi Araki, Jeny Rajan, John R. Laird, Andrew Nicolaides, Jasjit S. Suri:
State-of-the-art review on automated lumen and adventitial border delineation and its measurements in carotid ultrasound. Comput. Methods Programs Biomed. 163: 155-168 (2018) - [c14]Sandeep N. Menon, V. B. Vineeth Reddy, A. Yeshwanth, B. N. Anoop, Jeny Rajan:
A Novel Deep Learning Approach for the Removal of Speckle Noise from Optical Coherence Tomography Images Using Gated Convolution-Deconvolution Structure. CVIP (2) 2018: 115-126 - [c13]T. Guru Pradeep Reddy, Kandiraju Sai Ashritha, T. M. Prajwala, G. N. Girish, Abhishek R. Kothari, Shashidhar G. Koolagudi, Jeny Rajan:
Retinal-Layer Segmentation Using Dilated Convolutions. CVIP (1) 2018: 279-292 - [c12]A. V. Narasimhadhan, Aman Sharma, Shashidhar G. Koolagudi, G. V. S. S. K. R. Naganjaneyulu, Sure Avinash, Vinay Peddireddy, N. Bal Kishan, Jeny Rajan:
Reconstruction of Edges from Fan-Beam Projections. TENCON 2018: 1278-1283 - 2017
- [j15]Jithin Gokul, Madhu S. Nair, Jeny Rajan:
Guided SAR image despeckling with probabilistic non local weights. Comput. Geosci. 109: 16-24 (2017) - [j14]Chetan L. Srinidhi, P. Aparna, Jeny Rajan:
Recent Advancements in Retinal Vessel Segmentation. J. Medical Syst. 41(4): 70:1-70:22 (2017) - [j13]Adithya H. K. Upadhya, Basavaraj Talawar, Jeny Rajan:
GPU implementation of non-local maximum likelihood estimation method for denoising magnetic resonance images. J. Real Time Image Process. 13(1): 181-192 (2017) - [j12]P. Krishna Kumar, Tadashi Araki, Jeny Rajan, Luca Saba, Francesco Lavra, Nobutaka Ikeda, Aditya M. Sharma, Shoaib Shafique, Andrew Nicolaides, John R. Laird, Ajay Gupta, Jasjit S. Suri:
Accurate lumen diameter measurement in curved vessels in carotid ultrasound: an iterative scale-space and spatial transformation approach. Medical Biol. Eng. Comput. 55(8): 1415-1434 (2017) - [j11]P. V. Sudeep, Palanisamy Ponnusamy, Chandrasekharan Kesavadas, Jan Sijbers, Arnold J. den Dekker, Jeny Rajan:
A nonlocal maximum likelihood estimation method for enhancing magnetic resonance phase maps. Signal Image Video Process. 11(5): 913-920 (2017) - 2016
- [j10]P. V. Sudeep, Palanisamy Ponnusamy, Jeny Rajan, Hediyeh Baradaran, Luca Saba, Ajay Gupta, Jasjit S. Suri:
Speckle reduction in medical ultrasound images using an unbiased non-local means method. Biomed. Signal Process. Control. 28: 1-8 (2016) - [j9]P. V. Sudeep, S. Issac Niwas, Palanisamy Ponnusamy, Jeny Rajan, Yu Xiaojun, Xianghong Wang, Yuemei Luo, Linbo Liu:
Enhancement and bias removal of optical coherence tomography images: An iterative approach with adaptive bilateral filtering. Comput. Biol. Medicine 71: 97-107 (2016) - [j8]Rani Oomman Panicker, Biju Soman, Gagan Saini, Jeny Rajan:
A Review of Automatic Methods Based on Image Processing Techniques for Tuberculosis Detection from Microscopic Sputum Smear Images. J. Medical Syst. 40(1): 17:1-17:13 (2016) - [j7]Tadashi Araki, P. Krishna Kumar, Harman S. Suri, Nobutaka Ikeda, Ajay Gupta, Luca Saba, Jeny Rajan, Francesco Lavra, Aditya M. Sharma, Shoaib Shafique, Andrew Nicolaides, John R. Laird, Jasjit S. Suri:
Two Automated Techniques for Carotid Lumen Diameter Measurement: Regional versus Boundary Approaches. J. Medical Syst. 40(7): 182:1-182:19 (2016) - [c11]T. J. Narendra Rao, G. N. Girish, Jeny Rajan:
An Improved Contextual Information Based Approach for Anomaly Detection via Adaptive Inference for Surveillance Application. CVIP (1) 2016: 133-147 - [c10]G. N. Girish, Abhishek R. Kothari, Jeny Rajan:
Automated segmentation of intra-retinal cysts from optical coherence tomography scans using marker controlled watershed transform. EMBC 2016: 1292-1295 - 2015
- [j6]P. V. Sudeep, Palanisamy Ponnusamy, Chandrasekharan Kesavadas, Jeny Rajan:
Nonlocal linear minimum mean square error methods for denoising MRI. Biomed. Signal Process. Control. 20: 125-134 (2015) - [j5]P. Krishna Kumar, P. Darshan, Sheethal Kumar, Rahul Ravindra, Jeny Rajan, Luca Saba, Jasjit S. Suri:
Magnetic resonance image denoising using nonlocal maximum likelihood paradigm in DCT-framework. Int. J. Imaging Syst. Technol. 25(3): 256-264 (2015) - [j4]R. Riji, Jeny Rajan, Jan Sijbers, Madhu S. Nair:
Iterative bilateral filter for Rician noise reduction in MR images. Signal Image Video Process. 9(7): 1543-1548 (2015) - 2014
- [j3]Jeny Rajan, Arnold J. den Dekker, Jan Sijbers:
A new non-local maximum likelihood estimation method for Rician noise reduction in magnetic resonance images using the Kolmogorov-Smirnov test. Signal Process. 103: 16-23 (2014) - 2013
- [c9]P. V. Sudeep, Palanisamy Ponnusamy, Jeny Rajan:
A Hybrid Model for Rician Noise Reduction in MRI. ADCONS 2013: 56-61 - [c8]Jeny Rajan, Arnold J. den Dekker, Jaber Juntu, Jan Sijbers:
A New Nonlocal Maximum Likelihood Estimation Method for Denoising Magnetic Resonance Images. PReMI 2013: 451-458 - 2012
- [c7]Jeny Rajan, Johan Van Audekerke, Annemie van der Linden, Marleen Verhoye, Jan Sijbers:
An adaptive non local maximum likelihood estimation method for denoising magnetic resonance images. ISBI 2012: 1136-1139 - 2011
- [c6]Zhenhua Mai, Jeny Rajan, Marleen Verhoye, Jan Sijbers:
Robust edge-directed interpolation of magnetic resonance images. BMEI 2011: 472-476 - [c5]Jeny Rajan, Marleen Verhoye, Jan Sijbers:
A maximum likelihood estimation method for denoising magnitude MRI using restricted local neighborhood. Medical Imaging: Image Processing 2011: 79624U - 2010
- [c4]Jeny Rajan, Dirk H. J. Poot, Jaber Juntu, Jan Sijbers:
Segmentation Based Noise Variance Estimation from Background MRI Data. ICIAR (1) 2010: 62-70
2000 – 2009
- 2009
- [j2]Jeny Rajan, K. Kannan, Chandrasekharan Kesavadas, Bejoy Thomas:
Focal Cortical Dysplasia (FCD) lesion analysis with complex diffusion approach. Comput. Medical Imaging Graph. 33(7): 553-558 (2009) - [c3]Jeny Rajan, K. Kannan, M. R. Kaimal:
Smoothening and Sharpening Effects of Theta in Complex Diffusion for Image Processing. ICAPR 2009: 325-328 - [c2]Jeny Rajan, Ben Jeurissen, Jan Sijbers, K. Kannan:
Denoising Magnetic Resonance Images Using Fourth Order Complex Diffusion. IMVIP 2009: 123-127 - 2008
- [j1]Jeny Rajan, K. Kannan, M. R. Kaimal:
An Improved Hybrid Model for Molecular Image Denoising. J. Math. Imaging Vis. 31(1): 73-79 (2008) - 2006
- [c1]Jeny Rajan, M. R. Kaimal:
Speckle Reduction in Images with WEAD and WECD. ICVGIP 2006: 184-193
Coauthor Index
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last updated on 2024-08-07 22:25 CEST by the dblp team
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