Recent trend in medical imaging modalities and their applications in disease diagnosis: a review

B Abhisheka, SK Biswas, B Purkayastha, D Das… - Multimedia Tools and …, 2024 - Springer
Medical Imaging (MI) plays a crucial role in healthcare, including disease diagnosis,
treatment, and continuous monitoring. The integration of non-invasive techniques such as X …

Classification, detection, and segmentation performance of image-based AI in intracranial aneurysm: a systematic review

Z Zhou, Y Jin, H Ye, X Zhang, J Liu, W Zhang - BMC Medical Imaging, 2024 - Springer
Background The detection and management of intracranial aneurysms (IAs) are vital to
prevent life-threatening complications like subarachnoid hemorrhage (SAH). Artificial …

UNet deep learning architecture for segmentation of vascular and non-vascular images: a microscopic look at UNet components buffered with pruning, explainable …

JS Suri, M Bhagawati, S Agarwal, S Paul… - Ieee …, 2022 - ieeexplore.ieee.org
Biomedical image segmentation (BIS) task is challenging due to the variations in organ
types, position, shape, size, scale, orientation, and image contrast. Conventional methods …

Deep learning-based recognition and segmentation of intracranial aneurysms under small sample size

G Zhu, X Luo, T Yang, L Cai, JH Yeo, G Yan… - Frontiers in …, 2022 - frontiersin.org
The manual identification and segmentation of intracranial aneurysms (IAs) involved in the
3D reconstruction procedure are labor-intensive and prone to human errors. To meet the …

An extensive review on deep learning and machine learning intervention in prediction and classification of types of aneurysms

RA Sinnaswamy, N Palanisamy… - Wireless Personal …, 2023 - Springer
Aneurysm (Rupture of blood vessels) may happen in the cerebrum, abdominal aorta and
thoracic aorta of humans, which has a high fatal rate. The advancement of the artificial …

Automated detection of cerebral aneurysms on TOF-MRA using a deep learning approach: An external validation study

NC Lehnen, R Haase, FC Schmeel… - American Journal …, 2022 - Am Soc Neuroradiology
BACKGROUND AND PURPOSE: Cerebral aneurysms yield the risk of rupture, severe
disability and death. Thus, early detection of cerebral aneurysms is crucial to ensure timely …

Evaluation of the clinical application value of artificial intelligence in diagnosing head and neck aneurysms

Y Shen, C Zhu, B Chu, J Song, Y Geng, J Li, B Liu… - BMC Medical …, 2024 - Springer
Objective To evaluate the performance of a semi-automated artificial intelligence (AI)
software program (CerebralDoc® system) in aneurysm detection and morphological …

Impact of an AI software on the diagnostic performance and reading time for the detection of cerebral aneurysms on time of flight MR-angiography

NC Lehnen, AH Schievelkamp, C Gronemann… - Neuroradiology, 2024 - Springer
Purpose To evaluate the impact of an AI-based software trained to detect cerebral
aneurysms on TOF-MRA on the diagnostic performance and reading times across readers …

A medical disease assisted diagnosis method based on lightweight fuzzy SZGWO-ELM neural network model

Q Chen, C Zhang, T Peng, Y Pan, J Liu - Scientific Reports, 2024 - nature.com
The application of neural network model in intelligent diagnosis usually encounters
challenges such as continuous adjustment of network parameters and significant cost in …

Reproducibility and across-site transferability of an improved deep learning approach for aneurysm detection and segmentation in time-of-flight MR-angiograms

M Vach, L Wolf, D Weiss, VL Ivan, BB Hofmann… - Scientific Reports, 2024 - nature.com
This study aimed to (1) replicate a deep-learning-based model for cerebral aneurysm
segmentation in TOF-MRAs,(2) improve the approach by testing various fully automatic pre …