A5061120057- AI in cancer detection
- Digital Imaging for Blood Diseases
- Brain Tumor Detection and Classification
- Image and Signal Denoising Methods
- Medical Image Segmentation Techniques
- COVID-19 diagnosis using AI
- Advanced Image Fusion Techniques
- Radiomics and Machine Learning in Medical Imaging
- Optical Network Technologies
- Mathematical Dynamics and Fractals
- Advanced Photonic Communication Systems
- Cell Image Analysis Techniques
- Image Processing Techniques and Applications
- Lung Cancer Diagnosis and Treatment
- Advanced Neural Network Applications
- Photonic and Optical Devices
- Microwave Engineering and Waveguides
- Algorithms and Data Compression
- Low-power high-performance VLSI design
- Antenna Design and Analysis
- Smart Agriculture and AI
- Neural Networks and Applications
- Advanced Data Compression Techniques
- Advanced Fiber Laser Technologies
- Image Retrieval and Classification Techniques
Maulana Azad National Institute of Technology
2015-2024
AISECT University
2015
Across the globe, women suffer from breast cancer fatal disease. It is arising surprisingly due to a lack of awareness among them and inconvenient reach diagnostic systems. Many computer-aided systems have been developed for detection cancer. These quite lower performance, so more accurate diagnosis need time save life human beings. For large imbalanced image datasets, efficient learning network very important detect classify accurately. In this paper, graph based adaptive regularized deep...
Histopathology image segmentation is an important area in the field of computer aided diagnosis using processing. This study presents a local feature‐based novel technique for histopathology images. It mainly focuses on system that segments overlapped nuclei (OLN) without affecting general non‐OLN performance. The proposed method suggests three‐stage system. initial done by features demarcation regions. In second stage, salient‐based active contour applied complete nucleus‐region...
Image segmentation of magnetic resonance image (MRI) is a crucial process for visualisation and examination abnormal tissues, especially during clinical analysis. Complexity variations the tumour structure magnify challenges in automated detection brain MRIs. This study presents an automatic lesion recognition method MRI followed by classification. In proposed multistage method, intent region initialisation performed using low‐level information keypoint descriptors. A set linear filter used...
Abstract Breast cancer is a worldwide fatal disease that exists mostly among women. The deep learning technique has proven its effectiveness, but the performance of existing systems quite compromising. In this work, transfer system suggested for efficient breast classification from histopathology images. This based on novel multi‐level progressive feature aggregation (MPFA) and spatial domain approach. combination pretrained Resnet101 backbone network with MPFA implemented to extract more...
Breast cancer is a major public health issue that may be remedied with early identification and efficient organ therapy. The diagnosis prognosis of severe serious illnesses are likely to followed examined by biopsy the affected in order identify classify malignin cells or tissues. histopathology tissue one advancements modern medicine for breast cancer. Haematoxylin eosin staining slides used pathologists benign malignant clinical instances invasive A digital whole slide imaging (WSI)...
This paper presents the design of a Microstrip Log Periodic Dipole Array (MLPDA) antenna for wireless communication in C band. A simplest structure edge fed is chosen as base design. The parameters proposed are identified by investigating effect variation geometrical on gain and bandwidth. scale factor (τ) spacing (σ) defined accordingly imposed, order to create variations these parameters. Complexity parametric involved has been observed through change bandwidth realized MPLDA. transmission...
Image fusion has lots of application in real life to furnish a combined form many oriented objects different images into single image.Adaptive Fuzzy logic model with local level processing is controlling tool image characteristics accurately and been successfully applied large number applications.In this paper an adaptive fuzzy have proposed for multi-exposure multi-sensor images.Experimental results demonstrate the superiority method; it offers approximately 30%-35% improvement Universal...