[Retracted] Deep Neural Networks for Medical Image Segmentation
P Malhotra, S Gupta, D Koundal… - Journal of …, 2022 - Wiley Online Library
Image segmentation is a branch of digital image processing which has numerous
applications in the field of analysis of images, augmented reality, machine vision, and many …
applications in the field of analysis of images, augmented reality, machine vision, and many …
[HTML][HTML] An anatomization on breast cancer detection and diagnosis employing multi-layer perceptron neural network (MLP) and Convolutional neural network (CNN)
M Desai, M Shah - Clinical eHealth, 2021 - Elsevier
This paper aims to review Artificial neural networks, Multi-Layer Perceptron Neural network
(MLP) and Convolutional Neural network (CNN) employed to detect breast malignancies for …
(MLP) and Convolutional Neural network (CNN) employed to detect breast malignancies for …
Development and validation of a deep learning–based automated detection algorithm for major thoracic diseases on chest radiographs
Importance Interpretation of chest radiographs is a challenging task prone to errors,
requiring expert readers. An automated system that can accurately classify chest …
requiring expert readers. An automated system that can accurately classify chest …
YOLO based breast masses detection and classification in full-field digital mammograms
Abstract Background and Objective With the recent development in deep learning since
2012, the use of Convolutional Neural Networks (CNNs) in bioinformatics, especially …
2012, the use of Convolutional Neural Networks (CNNs) in bioinformatics, especially …
A new approach for classifying coronavirus COVID-19 based on its manifestation on chest X-rays using texture features and neural networks
S Varela-Santos, P Melin - Information sciences, 2021 - Elsevier
Since the recent challenge that humanity is facing against COVID-19, several initiatives
have been put forward with the goal of creating measures to help control the spread of the …
have been put forward with the goal of creating measures to help control the spread of the …
An automatic method for lung segmentation and reconstruction in chest X-ray using deep neural networks
JC Souza, JOB Diniz, JL Ferreira, GLF Da Silva… - Computer methods and …, 2019 - Elsevier
Abstract Background and Objective Chest X-ray (CXR) is one of the most used imaging
techniques for detection and diagnosis of pulmonary diseases. A critical component in any …
techniques for detection and diagnosis of pulmonary diseases. A critical component in any …
Chest X-ray analysis empowered with deep learning: A systematic review
Chest radiographs are widely used in the medical domain and at present, chest X-radiation
particularly plays an important role in the diagnosis of medical conditions such as …
particularly plays an important role in the diagnosis of medical conditions such as …
A deep learning approach for the analysis of masses in mammograms with minimal user intervention
We present an integrated methodology for detecting, segmenting and classifying breast
masses from mammograms with minimal user intervention. This is a long standing problem …
masses from mammograms with minimal user intervention. This is a long standing problem …
Automatic tuberculosis screening using chest radiographs
Tuberculosis is a major health threat in many regions of the world. Opportunistic infections in
immunocompromised HIV/AIDS patients and multi-drug-resistant bacterial strains have …
immunocompromised HIV/AIDS patients and multi-drug-resistant bacterial strains have …
Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration
The National Library of Medicine (NLM) is developing a digital chest X-ray (CXR) screening
system for deployment in resource constrained communities and developing countries …
system for deployment in resource constrained communities and developing countries …