Ajay Mittal

Ajay Mittal
Panjab University · University Institute of Engineering and Technology

About

39
Publications
8,917
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
697
Citations

Publications

Publications (39)
Article
Full-text available
Contactless fingerprint recognition has gained attention due to its data security and hygiene as compared to the contact-based counterpart. In the previous years, deep learning models, mainly Convolutional Neural Networks (CNNs), have been extensively applied in this field and have given promising results. Recently, their successor, Vision Transfor...
Article
Full-text available
Effective image denoising is vital for accurate biomedical image analysis, serving as a foundational step for subsequent diagnostic and analytical tasks. Medical diagnostic instruments often introduce noise during image acquisition, necessitating robust denoising algorithms to ensure diagnostic accuracy. Although deep learning has shown potential i...
Article
The prevalence of skin cancer has been increasing for the last few decades. Abnormal growth of cells forms skin lesions, which if not treated at the earliest, may turn into cancer. With the advancement in technology, computer-aided or remote diagnosis is possible, but a lot of efforts are required. An exclusive survey of the work done is required t...
Article
Full-text available
Deep learning and advancements in computer vision offer significant potential for analyzing medical images resulting in better healthcare and improved patient outcomes. Currently, the dominant approaches in the field of machine learning are supervised learning and transfer learning. These methods are not only prevalent in medicine and healthcare bu...
Article
Full-text available
Lung cancer, the second most prevalent form of cancer with the highest mortality rate, necessitates the stratification of patients based on their survival rates to develop effective treatment strategies. This study presents a two-stage framework for predicting lung cancer survival. The initial stage, classification, focuses on forecasting the five-...
Article
Full-text available
Federated Learning is a promising technique for preserving data privacy that enables communication between distributed nodes without the need for a central server. Previously, data privacy concerns have made it challenging for firms to share large datasets in critical locations, as network data tampering is a potential risk. Federated Learning offe...
Article
Full-text available
Leukemia is one of the deadly cancers which spreads itself at an exponential rate and has a detrimental impact on leukocytes in the human blood. To automate the process of leukemia detection, researchers have utilized deep learning networks to analyze blood smear images. In our research, we have proposed the usage of networks that mimic the human b...
Article
Full-text available
Biometrics encloses the science of measuring human body characteristics and authorizing the user based on biometric modalities. Physiological and behavioural biometrics identifiers are the two kinds of biometrics. The present article i.e. Gender Classification system (GCS) is one of the most challenging and serviceable application among the many be...
Chapter
Anemia is a major health problem that primarily affects women and children worldwide. Early anemia detection in children is necessary, and non-invasive diagnostic methods are advised. The patterns of the conjunctiva’s pallor and the blood’s hemoglobin concentration is used to diagnose anemia. Computer-aided diagnosis systems facilitate the physicia...
Article
In this paper, the authors present an effort to recognize handwritten Gurumukhi place-names for use in postal automation. Five feature extraction techniques (zoning, horizontal peak extent, vertical peak extent, diagonal, and centroid) have been analyzed and optimized using Principal Component Analysis (PCA). Four classification methods (k-Nearest...
Article
Full-text available
Leukemia can be detected by an abnormal rise in the number of immature lymphocytes and by a decrease in the number of other blood cells. To diagnose leukemia, image processing techniques are utilized to examine microscopic peripheral blood smear (PBS) images automatically and swiftly. To the best of our knowledge, the initial step in subsequent pro...
Article
Full-text available
Deep learning models are considered a revolutionary learning paradigm in artificial intelligence and machine learning, piquing the interest of image recognition and computer vision experts. Because deep learning models have gained popularity and improved outcomes in the literature, this work provides a deep learning method based on a holistic appro...
Article
In this paper, the authors present an effort to recognize handwritten Gurumukhi place-names for use in postal automation. Five feature extraction techniques (zoning, horizontal peak extent, vertical peak extent, diagonal, and centroid) have been analyzed and optimized using Principal Component Analysis (PCA). Four classification methods (k-Nearest...
Article
Leukemia, a type of blood cancer, is amongst the most deadly cancers worldwide. Since it affects leukocytes in the bloodstream, fast and early detection of abnormal leukocytes is required. Thus, precise detection of leukemia highly relies on accurate segmentation of leukocytes from blood smear images. The segmentation process has become quite robus...
Article
Full-text available
Automatic radiological report generation (ARRG) smoothens the clinical workflow by speeding the report generation task. Recently, various deep neural networks (DNNs) have been used for report generation and have achieved promising results. Despite the impressive results, their deployment remains challenging because of their size and complexity. Res...
Preprint
Full-text available
The segmentation of brain tumours plays a significant role in the analysis of medical imaging. For a precise diagnosis of the condition, radiologists employ medical imaging. In order to recognise brain tumours from medical imaging, the radiologist's work must be challenging and complex. There are various distinct steps that may be used to identify...
Preprint
Full-text available
Purpose: Leukemia can be detected by an abnormal rise in the number of immature lymphocytes and by a decrease in the number of other blood cells. To diagnose the existence of leukemia, image processing techniques are utilized to examine microscopic peripheral blood smear (PBS) images automatically and swiftly. Methods: To the best of our knowledge,...
Article
Full-text available
Generation of a clear, correct, concise, complete, and coherent linguistic description of the visual patterns in a medical image is a challenging task. Unfortunately, many radiologists fail to satisfactorily perform this task due to various reasons such as workload, scant time, and fatigue. Although AI-based computer-aided detection (CADe) and comp...
Article
Background Automated generation of radiological reports for different imaging modalities is essentially required to smoothen the clinical workflow and alleviate radiologists’ workload. It involves the careful amalgamation of image processing techniques for medical image interpretation and language generation techniques for report generation. This p...
Article
Leukemia, the cancer of blood-forming tissues, becomes fatal if not detected in the early stages. It is detected through a blood smear test that involves the morphological analysis of the stained blood slide. The manual microscopic examination of slides is tedious, time-consuming, error-prone, and subject to inter-observer and intra-observer bias....
Preprint
Full-text available
Segmentation of blood cells is a prerequisite step in automated morphological analysis of blood smear images, cell count determination and diagnosis of various diseases such as leukemia. It is extremely challenging due to different sizes, shapes, morphological characteristics and overlapping of blood cells. Due to its complicated nature, it is gene...
Chapter
Acute Lymphoblastic Leukemia (ALL) is one of the most commonly occurring type of leukemia which poses a serious threat to life. It severely affects White Blood Cells (WBCs) of the human body that fight against any kind of infection or disease. Since, there are no evident morphological changes and the signs are pretty similar to other disorders, it...
Conference Paper
The aim of this paper is to perform segmentation of white blood cells (WBCs) using blood smear images with the help of image processing techniques. Traditionally, the process of morphological analysis of cells is performed by a medical expert. This process is quite tedious and time consuming. The equipments used to perform the experiments are very...
Article
Full-text available
Image denoising is a thoroughly studied research problem in the areas of image processing and computer vision. In this work, a deep convolution neural network with added benefits of residual learning for image denoising is proposed. The network is composed of convolution layers and ResNet blocks along with rectified linear unit activation functions...
Article
Full-text available
Pulmonary tuberculosis (PTB) is a contagious disease that affects the lung region. PTB is a life-threatening disease if it is detected late or left untreated. To perform the initial screening of PTB, the World Health Organization has recommended chest radiograph. Till now, the screening process requires either the patients to come to secondary heal...
Article
Full-text available
Tuberculosis (TB) is an infectious disease that mainly affects the lung region. Its initial screening is mostly performed using chest radiograph, which is also recommended by the World Health Organization. To help the radiologists in diagnosing this disease, different computer-aided diagnosis (CAD) systems have been developed. However, the developm...
Chapter
Denoising is an important image pre-processing operation required to improve the image quality. In the past, several image denoising solutions have been put forth with varying performances. Recently, deep-learning based approaches have given better results than conventional algorithms. While these methods offer promising results on denoising of nat...
Article
Full-text available
Recognition of an object from an image or image sequences is an important task in computer vision. It is an important low-level image processing operation and plays a crucial role in many real-world applications. The challenges involved in object recognition are multi-model, multi-pose, complicated background, and depth variations. Recently develop...
Article
Full-text available
Automated segmentation of medical images that aims at extracting anatomical boundaries is a fundamental step in any computer-aided diagnosis (CAD) system. Chest radiographic CAD systems, which are used to detect pulmonary diseases, first segment the lung field to precisely define the region-of-interest from which radiographic patterns are sought. I...
Article
Full-text available
Automatic analysis of chest radiographs using computer-aided diagnosis (CAD) systems is pivotal to perform mass screening and detect early signs of various abnormalities in patients. In a chest radiographic CAD system, segmentation of lung fields is a pre-requisite step to precisely define region-of-interest and is subsequently used by other stages...
Article
Full-text available
Segmentation of lung fields is an important pre-requisite step in chest radiographic computer-aided diagnosis systems as it precisely defines the region-of-interest on which different operations are applied. However, it is immensely challenging due to extreme variations in shape and size of lungs. Manual segmentation is also prone to large inter-ob...
Article
Tuberculosis (TB) has become a global pandemic, and its eradication requires efficient screening methods, diagnostic tests, and effective drugs. Artificial intelligence-based computer-aided diagnostic (CADx) systems are purported to play a significant role in the mass screening of TB. The research on the development of CADx systems started four dec...
Chapter
Full-text available
Lung Field Segmentation (LFS) is an indispensable step for detecting austere lung diseases in various computer-aided diagnosis. This paper presents a deep learning-based Convolutional Neural Network (CNN) for segmenting lung fields in chest radiographs. The proposed CNN network consists of three sets of convolutional-layer and rectified linear unit...
Article
Lung field defines a region-of-interest in which specific radiologic signs such as septal lines, pulmonary opacities, cavities, consolidations, and lung nodules are searched by a chest radiographic computer-aided diagnostic system. Thus, its precise segmentation is extremely important. To precisely segment it, numerous methods have been developed d...
Article
Quick Response (QR) codes have become very popular in current scenario. Being machine readable, they appear like blocks of random black and white noise. With their increasing use in marketing material, many attempts have been made to make them visually appealing by embedding images and logos. We propose a colour image embedding method that uses cir...

Network

Cited By