Practical review on photoacoustic computed tomography using curved ultrasound array transducer
Photoacoustic computed tomography (PACT) has become a promising imaging modality
from laboratory to clinical research. Of many components of PACT system, the ultrasound …
from laboratory to clinical research. Of many components of PACT system, the ultrasound …
[HTML][HTML] Medical image-based computational fluid dynamics and fluid-structure interaction analysis in vascular diseases
Hemodynamic factors, induced by pulsatile blood flow, play a crucial role in vascular health
and diseases, such as the initiation and progression of atherosclerosis. Computational fluid …
and diseases, such as the initiation and progression of atherosclerosis. Computational fluid …
ME‐Net: multi‐encoder net framework for brain tumor segmentation
W Zhang, G Yang, H Huang, W Yang… - … Journal of Imaging …, 2021 - Wiley Online Library
MRI plays a vital role to evaluate brain tumor diagnosis and treatment planning. However,
the manual segmentation of the MRI image is strenuous. With the development of deep …
the manual segmentation of the MRI image is strenuous. With the development of deep …
Deep learning whole‐gland and zonal prostate segmentation on a public MRI dataset
Background Prostate volume, as determined by magnetic resonance imaging (MRI), is a
useful biomarker both for distinguishing between benign and malignant pathology and can …
useful biomarker both for distinguishing between benign and malignant pathology and can …
Deep learning-based methods for prostate segmentation in magnetic resonance imaging
Featured Application The study demonstrates that high-speed deep learning networks could
perform accurate prostate delineation facilitating the adoption of novel imaging parameters …
perform accurate prostate delineation facilitating the adoption of novel imaging parameters …
Customized efficient neural network for COVID-19 infected region identification in CT images
Background: In the field of biomedical imaging, radiomics is a promising approach that aims
to provide quantitative features from images. It is highly dependent on accurate identification …
to provide quantitative features from images. It is highly dependent on accurate identification …
An ensemble of global and local-attention based convolutional neural networks for COVID-19 diagnosis on chest X-ray images
The recent Coronavirus Disease 2019 (COVID-19) pandemic has put a tremendous burden
on global health systems. Medical practitioners are under great pressure for reliable …
on global health systems. Medical practitioners are under great pressure for reliable …
An automated liver tumour segmentation and classification model by deep learning based approaches
Liver cancer is regarded as one of the most common and leading causes of cancer death
around the world. Automatic liver tumour segmentation and classification techniques are …
around the world. Automatic liver tumour segmentation and classification techniques are …
Artificial intelligence and machine learning in aortic disease
LD Hahn, K Baeumler, A Hsiao - Current Opinion in Cardiology, 2021 - journals.lww.com
Multiple ML techniques have potential for characterization and risk prediction of aortic
aneurysm, dissection, coarctation, and atherosclerotic disease on computed tomography …
aneurysm, dissection, coarctation, and atherosclerotic disease on computed tomography …
Multiorgan segmentation from partially labeled datasets with conditional nnU-Net
G Zhang, Z Yang, B Huo, S Chai, S Jiang - Computers in Biology and …, 2021 - Elsevier
Accurate and robust multiorgan abdominal CT segmentation plays a significant role in
numerous clinical applications, such as therapy treatment planning and treatment delivery …
numerous clinical applications, such as therapy treatment planning and treatment delivery …