BTS-ST: Swin transformer network for segmentation and classification of multimodality breast cancer images
Breast cancer is considered the most commonly diagnosed cancer globally and falls second
to lung cancer. For the early detection of breast tumors in women, breast cancer analysis …
to lung cancer. For the early detection of breast tumors in women, breast cancer analysis …
Automatic detection of Covid-19 from chest X-ray and lung computed tomography images using deep neural networks and transfer learning
The world has been undergoing the most ever unprecedented circumstances caused by the
coronavirus pandemic, which is having a devastating global effect in different aspects of life …
coronavirus pandemic, which is having a devastating global effect in different aspects of life …
Joint diagnosis of pneumonia, COVID-19, and tuberculosis from chest X-ray images: A deep learning approach
Pneumonia, COVID-19, and tuberculosis are some of the most fatal and common lung
diseases in the current era. Several approaches have been proposed in the literature for the …
diseases in the current era. Several approaches have been proposed in the literature for the …
UNet: A semi-supervised method for segmentation of breast tumor images using a U-shaped pyramid-dilated network
Rapid and precise segmentation of breast tumors is a severe challenge for the global
research community to diagnose breast cancer in younger females. An ultrasound system is …
research community to diagnose breast cancer in younger females. An ultrasound system is …
Tuberculosis chest X-ray detection using CNN-based hybrid segmentation and classification approach
Tuberculosis still significantly impacts the world's population, with more than 10 million
people getting sick each year. Researchers have focused on developing computer-aided …
people getting sick each year. Researchers have focused on developing computer-aided …
A review of recent advances in deep learning models for chest disease detection using radiography
A Ait Nasser, MA Akhloufi - Diagnostics, 2023 - mdpi.com
Chest X-ray radiography (CXR) is among the most frequently used medical imaging
modalities. It has a preeminent value in the detection of multiple life-threatening diseases …
modalities. It has a preeminent value in the detection of multiple life-threatening diseases …
Multi-techniques for analyzing x-ray images for early detection and differentiation of pneumonia and tuberculosis based on hybrid features
An infectious disease called tuberculosis (TB) exhibits pneumonia-like symptoms and traits.
One of the most important methods for identifying and diagnosing pneumonia and …
One of the most important methods for identifying and diagnosing pneumonia and …
Drug-resistant tuberculosis treatment recommendation, and multi-class tuberculosis detection and classification using ensemble deep learning-based system
C Prasitpuriprecha, SS Jantama, T Preeprem… - Pharmaceuticals, 2022 - mdpi.com
This research develops the TB/non-TB detection and drug-resistant categorization diagnosis
decision support system (TB-DRC-DSS). The model is capable of detecting both TB …
decision support system (TB-DRC-DSS). The model is capable of detecting both TB …
[HTML][HTML] From pixels to pathology: employing computer vision to decode chest diseases in medical images
Radiology has been a pioneer in the healthcare industry's digital transformation,
incorporating digital imaging systems like picture archiving and communication system …
incorporating digital imaging systems like picture archiving and communication system …
A novel fusion model of hand-crafted features with deep convolutional neural networks for classification of several chest diseases using X-ray images
With the continuing global pandemic of coronavirus (COVID-19) sickness, it is critical to seek
diagnostic approaches that are both effective and rapid to limit the number of people …
diagnostic approaches that are both effective and rapid to limit the number of people …