We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
GLOBETECH PUBLISHING LLC

Download Mobile App




Deep Learning Aids in TB Detection via Smartphone

By MedImaging International staff writers
Posted on 07 Dec 2020
Image: TB can be detected via smartphone photos in resource poor settings (Photo courtesy of RSNA)
Image: TB can be detected via smartphone photos in resource poor settings (Photo courtesy of RSNA)
An artificial intelligence (AI) pattern recognition model can detect tuberculosis (TB) on phone-captured chest X-ray images.

The TBShoNet neural network, developed by researchers at the Massachusetts Institute of Technology (MIT, Cambridge, MA, USA) and National Cheng Kung University (NCKU; Tainan, Taiwan), was first pre-trained on a database containing 250,044 chest X-rays with 14 pulmonary labels, which did not include TB. The pre-trained model was then connected to an additional two-layer neural network trained on augmented chest X-ray images. It was then recalibrated for chest X-ray smartphone photographs by using simulation methods to augment the dataset.

Subsequently, 662 photographs of chest X-ray taken by five different phones (330 TB and 326 normal X-rays) were processed in order to test TBShoNet model performance. The results showed that sensitivity and specificity for TB classification were 81% and 84%, respectively. The study was presented at the Radiological Society of North America (RSNA) 106th Scientific Assembly and Annual Meeting, held online during November 2020.

“An early diagnosis of TB is crucial but challenging for resource-poor countries. TBShoNet provides a method to develop an algorithm that can be deployed on phones to assist healthcare providers in areas where radiologists and high-resolution digital images are unavailable,” said lead author and study presenter Po-Chih Kuo, PhD, of MIT and NCKU. “We need to extend the opportunities around medical artificial intelligence to resource-limited settings.”

TB is an infectious disease caused by the bacteria Mycobacterium tuberculosis. The disease primarily affects the lungs, but it can also affect other organs. Typical symptoms include persistent coughing (in which a person can bring up blood), weight loss, night sweats, a fever, tiredness and fatigue, and loss of appetite. TB is one of the most deadliest diseases in the world, since the bacteria can easily spread from person to person through airborne particles, and extensively drug-resistant (XDR) totally resistant TB types are becoming increasingly more common.

Related Links:
Massachusetts Institute of Technology
National Cheng Kung University


Computed Tomography System
Aquilion ONE / INSIGHT Edition
Digital Intelligent Ferromagnetic Detector
Digital Ferromagnetic Detector
Ultra-Flat DR Detector
meX+1717SCC
Portable X-ray Unit
AJEX140H

Channels

Ultrasound

view channel
Image: The new implantable device for chronic pain management is small and flexible (Photo courtesy of The Zhou Lab at USC)

Wireless Chronic Pain Management Device to Reduce Need for Painkillers and Surgery

Chronic pain affects millions of people globally, often leading to long-term disability and dependence on opioid medications, which carry significant risks of side effects and addiction.... Read more

Nuclear Medicine

view channel
Image: The diagnostic tool could improve diagnosis and treatment decisions for patients with chronic lung infections (Photo courtesy of SNMMI)

Novel Bacteria-Specific PET Imaging Approach Detects Hard-To-Diagnose Lung Infections

Mycobacteroides abscessus is a rapidly growing mycobacteria that primarily affects immunocompromised patients and those with underlying lung diseases, such as cystic fibrosis or chronic obstructive pulmonary... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible

Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.