[HTML][HTML] An overview of deep learning in medical imaging
A Anaya-Isaza, L Mera-Jiménez… - Informatics in medicine …, 2021 - Elsevier
Deep learning (DL) is one of the branches of artificial intelligence that has seen exponential
growth in recent years. The scientific community has focused its attention on DL due to its …
growth in recent years. The scientific community has focused its attention on DL due to its …
Explainable artificial intelligence (XAI) with IoHT for smart healthcare: A review
Discussing the use of artificial intelligence (AI) in healthcare, explainability is a highly
contentious topic. AI-powered systems may be superior at certain analytical tasks, but their …
contentious topic. AI-powered systems may be superior at certain analytical tasks, but their …
Synthetic data accelerates the development of generalizable learning-based algorithms for X-ray image analysis
Artificial intelligence (AI) now enables automated interpretation of medical images. However,
AI's potential use for interventional image analysis remains largely untapped. This is …
AI's potential use for interventional image analysis remains largely untapped. This is …
A systematic approach to deep learning-based nodule detection in chest radiographs
Lung cancer is a serious disease responsible for millions of deaths every year. Early stages
of lung cancer can be manifested in pulmonary lung nodules. To assist radiologists in …
of lung cancer can be manifested in pulmonary lung nodules. To assist radiologists in …
Fast template match algorithm for spatial object detection using a stereo vision system for autonomous navigation
O Real-Moreno, JC Rodríguez-Quiñonez… - Measurement, 2023 - Elsevier
The spatial object detection for autonomous navigation is an active research topic with many
works published about it, many of them use object detection and stereo vision systems to …
works published about it, many of them use object detection and stereo vision systems to …
Deep-learning-based automatic segmentation of parotid gland on computed tomography images
M Önder, C Evli, E Türk, O Kazan, İŞ Bayrakdar… - Diagnostics, 2023 - mdpi.com
This study aims to develop an algorithm for the automatic segmentation of the parotid gland
on CT images of the head and neck using U-Net architecture and to evaluate the model's …
on CT images of the head and neck using U-Net architecture and to evaluate the model's …
Chest X‐Ray Images to Differentiate COVID‐19 from Pneumonia with Artificial Intelligence Techniques
This paper presents an automated and noninvasive technique to discriminate COVID‐19
patients from pneumonia patients using chest X‐ray images and artificial intelligence. The …
patients from pneumonia patients using chest X‐ray images and artificial intelligence. The …
Software using artificial intelligence for nodule and cancer detection in CT lung cancer screening: systematic review of test accuracy studies
J Geppert, A Asgharzadeh, A Brown, C Stinton… - thorax, 2024 - thorax.bmj.com
Objectives To examine the accuracy and impact of artificial intelligence (AI) software
assistance in lung cancer screening using CT. Methods A systematic review of CE-marked …
assistance in lung cancer screening using CT. Methods A systematic review of CE-marked …
Simultaneous object detection and segmentation for patient‐specific markerless lung tumor tracking in simulated radiographs with deep learning
Background Real‐time tumor tracking is one motion management method to address motion‐
induced uncertainty. To date, fiducial markers are often required to reliably track lung tumors …
induced uncertainty. To date, fiducial markers are often required to reliably track lung tumors …
Anatomy-guided Pathology Segmentation
Pathological structures in medical images are typically deviations from the expected
anatomy of a patient. While clinicians consider this interplay between anatomy and …
anatomy of a patient. While clinicians consider this interplay between anatomy and …