Deep learning in medical image analysis
This review covers computer-assisted analysis of images in the field of medical imaging.
Recent advances in machine learning, especially with regard to deep learning, are helping …
Recent advances in machine learning, especially with regard to deep learning, are helping …
A review on lung boundary detection in chest X-rays
S Candemir, S Antani - … journal of computer assisted radiology and …, 2019 - Springer
Purpose Chest radiography is the most common imaging modality for pulmonary diseases.
Due to its wide usage, there is a rich literature addressing automated detection of …
Due to its wide usage, there is a rich literature addressing automated detection of …
Deep neural network ensemble for pneumonia localization from a large-scale chest x-ray database
Pneumonia is a bacterial, viral, or fungal infection of one or both sides of the lungs that
causes lung alveoli to fill up with fluid or pus, which is usually diagnosed with chest x-rays …
causes lung alveoli to fill up with fluid or pus, which is usually diagnosed with chest x-rays …
Fully convolutional architectures for multiclass segmentation in chest radiographs
AA Novikov, D Lenis, D Major… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
The success of deep convolutional neural networks (NNs) on image classification and
recognition tasks has led to new applications in very diversified contexts, including the field …
recognition tasks has led to new applications in very diversified contexts, including the field …
Segmentation and classification on chest radiography: a systematic survey
T Agrawal, P Choudhary - The Visual Computer, 2023 - Springer
Chest radiography (X-ray) is the most common diagnostic method for pulmonary disorders.
A trained radiologist is required for interpreting the radiographs. But sometimes, even …
A trained radiologist is required for interpreting the radiographs. But sometimes, even …
A deep learning based dual encoder–decoder framework for anatomical structure segmentation in chest X-ray images
Automated multi-organ segmentation plays an essential part in the computer-aided
diagnostic (CAD) of chest X-ray fluoroscopy. However, developing a CAD system for the …
diagnostic (CAD) of chest X-ray fluoroscopy. However, developing a CAD system for the …
LINKS: Learning-based multi-source IntegratioN frameworK for Segmentation of infant brain images
Segmentation of infant brain MR images is challenging due to insufficient image quality,
severe partial volume effect, and ongoing maturation and myelination processes. In the first …
severe partial volume effect, and ongoing maturation and myelination processes. In the first …
CX-Net: an efficient ensemble semantic deep neural network for ROI identification from chest-x-ray images for COPD diagnosis
AV Ikechukwu, S Murali - Machine Learning: Science and …, 2023 - iopscience.iop.org
Automatic identification of salient features in large medical datasets, particularly in chest x-
ray (CXR) images, is a crucial research area. Accurately detecting critical findings such as …
ray (CXR) images, is a crucial research area. Accurately detecting critical findings such as …
Image-to-images translation for multi-task organ segmentation and bone suppression in chest x-ray radiography
Chest X-ray radiography is one of the earliest medical imaging technologies and remains
one of the most widely-used for diagnosis, screening, and treatment follow up of diseases …
one of the most widely-used for diagnosis, screening, and treatment follow up of diseases …
Review of the applications of deep learning in bioinformatics
Y Zhang, J Yan, S Chen, M Gong, D Gao… - Current …, 2020 - ingentaconnect.com
Rapid advances in biological research over recent years have significantly enriched
biological and medical data resources. Deep learning-based techniques have been …
biological and medical data resources. Deep learning-based techniques have been …