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Jeny Rajan
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2020 – today
- 2024
- [j47]Rishi Raj
, Dayananda Pruthviraja
Multilevel Multimodal Framework for Automatic Collateral Scoring in Brain Stroke. IEEE Access 12: 33730-33748 (2024) - [j46]Siva Bonthada
An automated deep learning pipeline for detecting user errors in spirometry test. Biomed. Signal Process. Control. 90: 105845 (2024) - [j45]A. S. Neethi
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
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
A Deep Ensemble Learning-Based CNN Architecture for Multiclass Retinal Fluid Segmentation in OCT Images. IEEE Access 11: 17241-17251 (2023) - [j41]Rishi Raj
StrokeViT with AutoML for brain stroke classification. Eng. Appl. Artif. Intell. 119: 105772 (2023) - [j40]Tojo Mathew
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
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) - [c22]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
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
Crossover based technique for data augmentation. Comput. Methods Programs Biomed. 218: 106716 (2022) - [j33]S. Niyas, S. J. Pawan
Medical image segmentation with 3D convolutional neural networks: A survey. Neurocomputing 493: 397-413 (2022) - [j32]S. J. Pawan
Capsule networks for image classification: A review. Neurocomputing 509: 102-120 (2022) - [j31]Tojo Mathew
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
An empirical study of the impact of masks on face recognition. Pattern Recognit. 122: 108308 (2022) - [c21]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 - [c20]Dheeraj Kumar Srivastava, S. J. Pawan
An Automated Approach for Screening COVID-19 from Thermal Images Using Convolutional Neural Network. AIIIMA/MIABID@MICCAI 2022: 83-91 - [c19]Govind Jeevan, S. J. Pawan
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
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
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
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) - [c18]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
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
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
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
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
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
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) - [c17]T. J. Narendra Rao, G. N. Girish
Deep Learning Based Sub-Retinal Fluid Segmentation in Central Serous Chorioretinopathy Optical Coherence Tomography Scans. EMBC 2019: 978-981 - [c16]G. N. Girish
Depthwise Separable Convolutional Neural Network Model for Intra-Retinal Cyst Segmentation. EMBC 2019: 2027-2031 - 2018
- [j20]Wadageri Yamanappa
Non-Local Means Image Denoising Using Shapiro-Wilk Similarity Measure. IEEE Access 6: 66914-66922 (2018) - [j19]Y. Nagaraj, Pardhu Madipalli, Jeny Rajan
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
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
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
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) - [c15]Sandeep N. Menon, V. B. Vineeth Reddy, A. Yeshwanth, B. N. Anoop
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 - [c14]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 - [c13]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
Guided SAR image despeckling with probabilistic non local weights. Comput. Geosci. 109: 16-24 (2017) - [j14]Chetan L. Srinidhi
Recent Advancements in Retinal Vessel Segmentation. J. Medical Syst. 41(4): 70:1-70:22 (2017) - [j13]Adithya H. K. Upadhya, Basavaraj Talawar
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
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
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
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
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
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
Two Automated Techniques for Carotid Lumen Diameter Measurement: Regional versus Boundary Approaches. J. Medical Syst. 40(7): 182:1-182:19 (2016) - [c12]T. J. Narendra Rao, G. N. Girish
An Improved Contextual Information Based Approach for Anomaly Detection via Adaptive Inference for Surveillance Application. CVIP (1) 2016: 133-147 - [c11]G. N. Girish
Automated segmentation of intra-retinal cysts from optical coherence tomography scans using marker controlled watershed transform. EMBC 2016: 1292-1295 - [c10]R. Soorajkumar, P. Krishna Kumar, D. Girish, Jeny Rajan:
Fourth order PDE based ultrasound despeckling using ENI classification. SPCOM 2016: 1-5 - 2015
- [j6]P. V. Sudeep
Nonlocal linear minimum mean square error methods for denoising MRI. Biomed. Signal Process. Control. 20: 125-134 (2015) - [j5]P. Krishna Kumar
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
Iterative bilateral filter for Rician noise reduction in MR images. Signal Image Video Process. 9(7): 1543-1548 (2015) - 2014
- [j3]Jeny Rajan
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
A Hybrid Model for Rician Noise Reduction in MRI. ADCONS 2013: 56-61 - [c8]Jeny Rajan
A New Nonlocal Maximum Likelihood Estimation Method for Denoising Magnetic Resonance Images. PReMI 2013: 451-458 - 2012
- [c7]Jeny Rajan
An adaptive non local maximum likelihood estimation method for denoising magnetic resonance images. ISBI 2012: 1136-1139 - 2011
- [c6]Zhenhua Mai, Jeny Rajan
Robust edge-directed interpolation of magnetic resonance images. BMEI 2011: 472-476 - [c5]Jeny Rajan
A maximum likelihood estimation method for denoising magnitude MRI using restricted local neighborhood. Medical Imaging: Image Processing 2011: 79624U - 2010
- [c4]Jeny Rajan
Segmentation Based Noise Variance Estimation from Background MRI Data. ICIAR (1) 2010: 62-70
2000 – 2009
- 2009
- [j2]Jeny Rajan
Focal Cortical Dysplasia (FCD) lesion analysis with complex diffusion approach. Comput. Medical Imaging Graph. 33(7): 553-558 (2009) - [c3]Jeny Rajan
Smoothening and Sharpening Effects of Theta in Complex Diffusion for Image Processing. ICAPR 2009: 325-328 - [c2]Jeny Rajan
Denoising Magnetic Resonance Images Using Fourth Order Complex Diffusion. IMVIP 2009: 123-127 - 2008
- [j1]Jeny Rajan
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 2024-11-22 19:42 CET by the dblp team
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