A comprehensive survey to study the utilities of image segmentation methods in clinical routine
The clinicians usually desire to know the shape of the liver during treatment planning to
minimize the damage to the surrounding healthy tissues and hepatic vessels, thus, building …
minimize the damage to the surrounding healthy tissues and hepatic vessels, thus, building …
Toward human intervention-free clinical diagnosis of intracranial aneurysm via deep neural network
Intracranial aneurysm (IA) is an enormous threat to human health, which often results in
nontraumatic subarachnoid hemorrhage or dismal prognosis. Diagnosing IAs on commonly …
nontraumatic subarachnoid hemorrhage or dismal prognosis. Diagnosing IAs on commonly …
Multiple regulation and targeting effects of borneol in the neurovascular unit in neurodegenerative diseases
N Chen, J Wen, Z Wang, J Wang - Basic & Clinical …, 2022 - Wiley Online Library
Efficient delivery of brain‐targeted drugs is highly important for the success of therapies in
neurodegenerative diseases. Borneol has several biological activities, such as anti …
neurodegenerative diseases. Borneol has several biological activities, such as anti …
StrokeNet: An automated approach for segmentation and rupture risk prediction of intracranial aneurysm
Intracranial Aneurysms (IA) present a complex challenge for neurosurgeons as the risks
associated with surgical intervention, such as Subarachnoid Hemorrhage (SAH) mortality …
associated with surgical intervention, such as Subarachnoid Hemorrhage (SAH) mortality …
Moving object tracking in clinical scenarios: application to cardiac surgery and cerebral aneurysm clip**
SP Dakua, J Abinahed, A Zakaria… - International Journal of …, 2019 - Springer
Background and objectives Surgical procedures such as laparoscopic and robotic surgeries
are popular since they are invasive in nature and use miniaturized surgical instruments for …
are popular since they are invasive in nature and use miniaturized surgical instruments for …
Pretrained subtraction and segmentation model for coronary angiograms
Y Zeng, H Liu, J Hu, Z Zhao, Q She - Scientific Reports, 2024 - nature.com
This study introduces a novel self-supervised learning method for single-frame subtraction
and vessel segmentation in coronary angiography, addressing the scarcity of annotated …
and vessel segmentation in coronary angiography, addressing the scarcity of annotated …
A diagnosis model for detection and classification of diabetic retinopathy using deep learning
Diabetes mellitus (DM) is an immense progressive disease that affects the usage of blood
glucose as energy, resulting in surplus glucose in the blood. If prolonged diabetes, it causes …
glucose as energy, resulting in surplus glucose in the blood. If prolonged diabetes, it causes …
Hypoxia-based classification and prognostic signature for clinical management of hepatocellular carcinoma
K Li, Y Yang, M Ma, S Lu, J Li - World Journal of Surgical Oncology, 2023 - Springer
Objective Intratumoral hypoxia is an essential feature of hepatocellular carcinoma (HCC).
Herein, we investigated the hypoxia-based heterogeneity and relevant clinical implication in …
Herein, we investigated the hypoxia-based heterogeneity and relevant clinical implication in …
Real-time detection of track fasteners based on object detection and FPGA
T **ao, T Xu, G Wang - Microprocessors and Microsystems, 2023 - Elsevier
An accurate and fast fasteners detection is of great significance for improving the inspection
efficiency of railway tracks. However, the task is also challenging due to the limited memory …
efficiency of railway tracks. However, the task is also challenging due to the limited memory …
Comprehensive assessment of imaging quality of artificial intelligence-assisted compressed sensing-based MR images in routine clinical settings
A Karthik, K Aggarwal, A Kapoor, D Singh, L Hu… - BMC Medical …, 2024 - Springer
Background Conventional MR acceleration techniques, such as compressed sensing,
parallel imaging, and half Fourier often face limitations, including noise amplification …
parallel imaging, and half Fourier often face limitations, including noise amplification …