Priyank Saxena

@bitmesra.ac.in

Assistanat Professor, ECE
Birla Institute of Technology, Mesra, Ranchi

Priyank Saxena


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https://researchid.co/priyank

RESEARCH, TEACHING, or OTHER INTERESTS

Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Human-Computer Interaction
12

Scopus Publications

55

Scholar Citations

4

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • Pathologic myopia diagnosis and localization from retinal fundus images using custom CNN
    Pammi Kumari, Priyank Saxena
    Neural Computing and Applications, 2024
  • An efficient multitasking cascade network for arteriovenous segmentation using dual-modal fundus images
    Rajnish Kumar Diwakar, Pammi Kumari, Priyank Saxena, Raju Poddar
    Multimedia Tools and Applications, 2024
  • Disease localization and its prediction from retinal fundus images using explicitly designed deep learning architecture
    Pammi Kumari, Priyank Saxena
    Multimedia Tools and Applications, 2024
  • Automated Diabetic Retinopathy Grading based on the Modified Capsule Network Architecture
    Pammi Kumari, Priyank Saxena
    IETE Journal of Research, 2024
    The most significant source of eye disease is Diabetic Retinopathy (DR) among individuals who have had diabetes for a long time. Early or timely detection of DR stages is crucial for a better prognosis. The subtle distinction among different DR stages(level 0 to level 4) and many structures of varying shapes and sizes make manual recognition challenging and consume more time. Thus, this work focuses on the automatic grading of the retinal images (L-0 to L-4) based on the DR severity using a modified Capsule Network (Caps Net). The ability of Caps Net to capture spatial information of an object and the probability of some entity's existence in an image makes it more suitable for grading DR stages. This work proposes a hybrid model architecture that contains Caps Net followed by a Support Vector Machine(SVM) at its output layer. The main reason for incorporating an SVM at the output layer of Caps Net is to enhance SVM classification using automatic features extracted significantly but also alleviates the computational complexity of training and testing by the Caps Net model. The experiments were conducted on the APTOS 2019 Blindness Detection Data set. The investigation's outcome substantiates the proposed architecture's efficiency over the existing CNNs and Capsule Networks.
  • Cataract detection and visualization based on multi-scale deep features by RINet tuned with cyclic learning rate hyperparameter
    Pammi Kumari, Priyank Saxena
    Biomedical Signal Processing and Control, 2024
  • Retinal Disease Classification Using Custom CNN Model from OCT Images
    Snehil Baba, Pammi Kumari, Priyank Saxena
    Procedia Computer Science, 2024
    Retinal diseases affect the eye’s retina and are the leading cause of vision loss. Timely detection and diagnosis can provide more treatment options and preserve vision. Retinal imaging, such as Optical Coherence Tomography (OCT), is used for screening patients and enables clinicians to visualize the retinal layers in detail, helping in early diagnosis and tailoring appropriate treatment plans. This study uses OCT images to detect diseases related to macular disorders common in old age. A custom convolution Neural Network (CNN) model is proposed in this study to classify OCT images of normal, choroidal neovascularization (CNV), diabetic macular edema (DME), and Drusen from a public dataset. Experiments were conducted using conventional machine learning (ML) and transfer learning-based models other than the proposed one. The proposed model performed favorably, attaining the training and validation accuracy of 97% and 93%, respectively. The proposed model achieves a testing accuracy of 98% with a loss of 0.051 and outperforms the existing models compared to this study.
  • Automated detection and multi-stage classification of diabetic retinopathy through CNN
    Pammi Kumari, Priyank Saxena
    Aip Conference Proceedings, 2023
  • PathologicMyopia Detection and Visualization Based on Multi-Scale Deep Features by PMnet Tuned with Cyclic Learning Rate Hyperparameter
    P. Kumari, P. Saxena
    Iet Conference Proceedings, 2023
    Pathologic Myopia (PM) is one of the factors of irreversible visual artifacts and puts patients at risk of other severe retinal diseases. Early intervention can help control the disease's progression and avert vision loss. Due to its prevalence worldwide, automated detection of PM and its severity is essential. Deep-learning (DL) based diagnosis has proven itself in the field of ophthalmology. The proposed study automatically classifies pathologic and non-Pathologic Myopia from the fundus images using an autoencoder for feature extraction integrated with Convolutional Neural Network (PMnet) explicitly designed for fundus images.
  • Efficient Restoration of Magnetic Resonance Images Corrupted with Impulse Noise using Spatial Constraints based Fuzzy Decision Filter
    Priyank Saxena, Rajive Kumar
    Journal of Scientific and Industrial Research, 2023
    Magnetic Resonance (MR) images are subject to unavoidable noises during the data acquisition due to imperfections of device components and trade-offs in the scan parameters. The study proposes a two-step Fuzzy Decision-Based Filter (FDBF) as a post-reconstruction technique to mitigate random valued impulse noise from MR images. The FDBF employs a Spatial Fuzzy C-means (SFCM) clustering for detection and an Intensity Based Fuzzy Estimation (IBFE) technique for restoration. Firstly, SFCM integrates the spatial relation of the adjacent pixels into the membership function to form three separate clusters. The IBFE technique leaves the noise-free cluster unaltered while restoring the remaining in the second step. IBFE incorporates neighbor pixel correlation to restore the corrupted pixel leading to edge preservation. To assess the efficacy of the intended method both the quality metrics and the observed quality of the restored images are considered. The suggested detection strategy using SFCM performs very well, up to a 93% corruption level with zero false and miss detection rates even when there is intensity in homogeneity among pixels. Compared to other existing filtering techniques, the proposed two-step restoration method significantly improves the perceived image quality and other image quality metrics of the restored image without obliterating more intricate details and finer structures. FDBF considers the spatial information of the nearby pixels during the detection and restoration processes, which is essential for MR image restoration.
  • Quantification of Cartilage loss for Automatic Detection and Classification of Osteoarthritis using Machine Learning approach
    Abhinav Kumar, Priyank Saxena
    2019 10th International Conference on Computing Communication and Networking Technologies Icccnt 2019, 2019
    Knee Osteoarthritis (OA) is musculoskeletal ailment and a measure cause of chronic disability. It is well known that the plain radiographs fail to detect the early OA changes and the best possible way to measure its progression is to quantify the articular cartilage loss. In this work, a computer aided diagnosis method using machine learning approach is proposed to predict knee OA severity from the radiographs based on the Ahlbäck grading scale. To achieve this objective, the loss of articular cartilage is quantified by measuring the minimum joint space width and is used for classifying OA to different classes. Different supervised classifiers such as KNN, SVM and Random forest are tested on Osteoarthritis initiative data set. KNN yields the highest accuracy among them. The results validates the effectiveness of the proposed method when compared with other existing methods and achieves an accuracy of 97%.
  • A locally adaptive edge preserving filter for denoising of low dose CT using multi-level fuzzy reasoning concept
    Priyank Saxena, R. Sukesh Kumar
    International Journal of Biomedical Engineering and Technology, 2019
  • GCD Based Blind Super-Resolution for Remote Sensing Applications
    Neerav Sharma, Praina Parimita Dash, Priyank Saxena
    2nd International Conference on Energy Power and Environment Towards Smart Technology Icepe 2018, 2018

RECENT SCHOLAR PUBLICATIONS

  • A CONVOLUTIONAL AUTOENCODER-BASED CATARACT CLASSIFICATION AND DISEASE LOCALISATION USING FUNDUS IMAGES
    P SAXENA, P KUMARI
    INTERNATIONAL JOURNAL 1 (1) , 2025
    2025
  • Pathologic myopia diagnosis and localization from retinal fundus images using custom CNN
    P Kumari, P Saxena
    Neural Computing and Applications 36 (23), 14309-14325 , 2024
    2024
    Citations: 4
  • An efficient multitasking cascade network for arteriovenous segmentation using dual-modal fundus images
    RK Diwakar, P Kumari, P Saxena, R Poddar
    Multimedia tools and applications 83 (16), 48399-48414 , 2024
    2024
    Citations: 2
  • Automated diabetic retinopathy grading based on the modified capsule network architecture
    P Kumari, P Saxena
    IETE Journal of Research 70 (3), 2917-2928 , 2024
    2024
    Citations: 5
  • Disease localization and its prediction from retinal fundus images using explicitly designed deep learning architecture
    P Kumari, P Saxena
    Multimedia Tools and Applications 83 (10), 28461-28478 , 2024
    2024
    Citations: 2
  • Retinal disease classification using custom cnn model from oct images
    S Baba, P Kumari, P Saxena
    Procedia Computer Science 235, 3142-3152 , 2024
    2024
    Citations: 14
  • Cataract detection and visualization based on multi-scale deep features by RINet tuned with cyclic learning rate hyperparameter
    P Kumari, P Saxena
    Biomedical Signal Processing and Control 87, 105452 , 2024
    2024
    Citations: 10
  • PathologicMyopia detection and visualization based on multi-scale deep features by PMnet tuned with cyclic learning rate hyperparameter
    P Kumari, P Saxena
    IET Conference Proceedings CP832 2023 (5), 346-355 , 2023
    2023
  • Automated detection and multi-stage classification of diabetic retinopathy through CNN
    P Kumari, P Saxena
    INTERNATIONAL CONFERENCE ON APPLIED COMPUTATIONAL INTELLIGENCE AND ANALYTICS … , 2023
    2023
    Citations: 1
  • Efficient Restoration of Magnetic Resonance Images Corrupted with Impulse Noise using Spatial Constraints based Fuzzy Decision Filter: SPATIAL CONSTRAINT BASED FUZZY DECISION …
    P Saxena, RS Kumar
    Journal of Scientific & Industrial Research (JSIR) 82 (06), 642-651 , 2023
    2023
  • Quantification of cartilage loss for automatic detection and classification of osteoarthritis using machine learning approach
    A Kumar, P Saxena
    2019 10th international conference on computing, communication and … , 2019
    2019
    Citations: 11
  • A locally adaptive edge preserving filter for denoising of low dose CT using multi-level fuzzy reasoning concept
    P Saxena, RS Kumar
    International Journal of Biomedical Engineering and Technology 31 (4), 388-404 , 2019
    2019
    Citations: 2
  • GCD Based Blind Super-Resolution for Remote Sensing Applications
    N Sharma, PP Dash, P Saxena
    2018 2nd International Conference on Power, Energy and Environment: Towards … , 2018
    2018
  • Restoration of CT images corrupted with fixed valued impulse noise using an optimum decision-based filter
    P Saxena, RS Kumar
    Intelligent Multidimensional Data and Image Processing, 220-239 , 2018
    2018
    Citations: 2
  • An Effective Filter for Noise Removal in Magnetic Resonance Images Using Multilevel Fuzzy Reasoning Concept
    P Saxena, RS Kumar
    Journal of Clinical Engineering 42 (3), 121-135 , 2017
    2017
    Citations: 2

MOST CITED SCHOLAR PUBLICATIONS

  • Retinal disease classification using custom cnn model from oct images
    S Baba, P Kumari, P Saxena
    Procedia Computer Science 235, 3142-3152 , 2024
    2024
    Citations: 14
  • Quantification of cartilage loss for automatic detection and classification of osteoarthritis using machine learning approach
    A Kumar, P Saxena
    2019 10th international conference on computing, communication and … , 2019
    2019
    Citations: 11
  • Cataract detection and visualization based on multi-scale deep features by RINet tuned with cyclic learning rate hyperparameter
    P Kumari, P Saxena
    Biomedical Signal Processing and Control 87, 105452 , 2024
    2024
    Citations: 10
  • Automated diabetic retinopathy grading based on the modified capsule network architecture
    P Kumari, P Saxena
    IETE Journal of Research 70 (3), 2917-2928 , 2024
    2024
    Citations: 5
  • Pathologic myopia diagnosis and localization from retinal fundus images using custom CNN
    P Kumari, P Saxena
    Neural Computing and Applications 36 (23), 14309-14325 , 2024
    2024
    Citations: 4
  • An efficient multitasking cascade network for arteriovenous segmentation using dual-modal fundus images
    RK Diwakar, P Kumari, P Saxena, R Poddar
    Multimedia tools and applications 83 (16), 48399-48414 , 2024
    2024
    Citations: 2
  • Disease localization and its prediction from retinal fundus images using explicitly designed deep learning architecture
    P Kumari, P Saxena
    Multimedia Tools and Applications 83 (10), 28461-28478 , 2024
    2024
    Citations: 2
  • A locally adaptive edge preserving filter for denoising of low dose CT using multi-level fuzzy reasoning concept
    P Saxena, RS Kumar
    International Journal of Biomedical Engineering and Technology 31 (4), 388-404 , 2019
    2019
    Citations: 2
  • Restoration of CT images corrupted with fixed valued impulse noise using an optimum decision-based filter
    P Saxena, RS Kumar
    Intelligent Multidimensional Data and Image Processing, 220-239 , 2018
    2018
    Citations: 2
  • An Effective Filter for Noise Removal in Magnetic Resonance Images Using Multilevel Fuzzy Reasoning Concept
    P Saxena, RS Kumar
    Journal of Clinical Engineering 42 (3), 121-135 , 2017
    2017
    Citations: 2
  • Automated detection and multi-stage classification of diabetic retinopathy through CNN
    P Kumari, P Saxena
    INTERNATIONAL CONFERENCE ON APPLIED COMPUTATIONAL INTELLIGENCE AND ANALYTICS … , 2023
    2023
    Citations: 1
  • A CONVOLUTIONAL AUTOENCODER-BASED CATARACT CLASSIFICATION AND DISEASE LOCALISATION USING FUNDUS IMAGES
    P SAXENA, P KUMARI
    INTERNATIONAL JOURNAL 1 (1) , 2025
    2025
  • PathologicMyopia detection and visualization based on multi-scale deep features by PMnet tuned with cyclic learning rate hyperparameter
    P Kumari, P Saxena
    IET Conference Proceedings CP832 2023 (5), 346-355 , 2023
    2023
  • Efficient Restoration of Magnetic Resonance Images Corrupted with Impulse Noise using Spatial Constraints based Fuzzy Decision Filter: SPATIAL CONSTRAINT BASED FUZZY DECISION …
    P Saxena, RS Kumar
    Journal of Scientific & Industrial Research (JSIR) 82 (06), 642-651 , 2023
    2023
  • GCD Based Blind Super-Resolution for Remote Sensing Applications
    N Sharma, PP Dash, P Saxena
    2018 2nd International Conference on Power, Energy and Environment: Towards … , 2018
    2018