Optimum laplacian wavelet mask based medical image using hybrid cuckoo search–grey wolf optimization algorithm
Multi scale masking techniques are well known in the field of multi modal medical image
fusion. In medical image fusion the quality of complement information is important. In multi …
fusion. In medical image fusion the quality of complement information is important. In multi …
An improved mammogram classification approach using back propagation neural network
A Gautam, V Bhateja, A Tiwari… - Data Engineering and …, 2018 - Springer
Mammograms are generally contaminated by quantum noise, degrading their visual quality
and thereby the performance of the classifier in Computer-Aided Diagnosis (CAD). Hence …
and thereby the performance of the classifier in Computer-Aided Diagnosis (CAD). Hence …
Haralick features-based classification of mammograms using SVM
V Bhateja, A Gautam, A Tiwari, LN Bao… - … Systems Design and …, 2018 - Springer
The contrast enhancement of mammograms at preprocessing stage optimizes the overall
performance of a computer-aided detection (CAD) system for breast cancer. In the proposed …
performance of a computer-aided detection (CAD) system for breast cancer. In the proposed …
[HTML][HTML] Local entropy maximization based image fusion for contrast enhancement of mammogram
Early detection of breast cancer can enhance the chances of survival. Contrast
enhancement provides improved visual information that can be used for accurate …
enhancement provides improved visual information that can be used for accurate …
Performance comparison of different wavelet families based on bone vessel fusion
A Dogra - Asian Journal of Pharmaceutics (AJP), 2016 - asiapharmaceutics.info
Aim: Image fusion has been a widely used application in the field of medical diagnosis.
Hence, a very little amount of literature has been found out on Bone and vascular image …
Hence, a very little amount of literature has been found out on Bone and vascular image …
Lesion-aware convolutional neural network for chest radiograph classification
F Li, JX Shi, L Yan, YG Wang, XD Zhang, MS Jiang… - Clinical Radiology, 2021 - Elsevier
AIM To investigate the performance of a deep-learning approach termed lesion-aware
convolutional neural network (LACNN) to identify 14 different thoracic diseases on chest X …
convolutional neural network (LACNN) to identify 14 different thoracic diseases on chest X …
Multi-scale Retinex with Chromacity Preservation (MSRCP)-Based Contrast Enhancement of Microscopy Images
V Bhateja, A Yadav, D Singh, BK Chauhan - Smart Intelligent Computing …, 2022 - Springer
Microscopy images are acquired by capturing the microscopic view of blood sample under a
microscope using a camera. The image quality is not that reliable further making bacteria …
microscope using a camera. The image quality is not that reliable further making bacteria …
CLAHE parameters effects on the quantitative and visual assessment of dense breast mammograms
PC Carneiro, CL Debs, AO Andrade… - IEEE Latin America …, 2019 - ieeexplore.ieee.org
In Brazil, breast cancer is the disease with the highest mortality rate in women, mainly due to
late diagnosis. The digital image processing has been used in order to provide both an …
late diagnosis. The digital image processing has been used in order to provide both an …
De-noising diseased plant leaf image
Health of the plant is of paramount concern in order to increase the agricultural productivity.
Diseases contribute considerably in lowering the productivity and yield quality. Hence, it is of …
Diseases contribute considerably in lowering the productivity and yield quality. Hence, it is of …
RICE: A method for quantitative mammographic image enhancement
F Janan, M Brady - Medical image analysis, 2021 - Elsevier
Abstract We introduce Region of Interest Contrast Enhancement (RICE) to identify focal
densities in mammograms. It aims to help radiologists: 1) enhancing the contrast of …
densities in mammograms. It aims to help radiologists: 1) enhancing the contrast of …