H-ProMed: Ultrasound image segmentation based on the evolutionary neural network and an improved principal curve
The purpose of this work is to develop a method for accurate and robust prostate
segmentation in transrectal ultrasound (TRUS) images. These images are difficult to …
segmentation in transrectal ultrasound (TRUS) images. These images are difficult to …
Focal modulation network for lung segmentation in chest X-ray images
Segmentation of lung regions is of key importance for the automatic analysis of Chest X-Ray
(CXR) images, which have a vital role in the detection of various pulmonary diseases …
(CXR) images, which have a vital role in the detection of various pulmonary diseases …
Simulating federated transfer learning for lung segmentation using modified UNet model
Lung segmentation helps doctors in analyzing and diagnosing lung diseases effectively.
Covid-19 pandemic highlighted the need for such artificial intelligence (AI) model to …
Covid-19 pandemic highlighted the need for such artificial intelligence (AI) model to …
Semi-supervised medical imaging segmentation with soft pseudo-label fusion
Segmentation is an essential task in modern medical imaging analysis. Since the scarcity of
labeled pixel-level annotations often limits its wide applications, recent studies have …
labeled pixel-level annotations often limits its wide applications, recent studies have …
Semi-automatic prostate segmentation from ultrasound images using machine learning and principal curve based on interpretable mathematical model expression
Accurate prostate segmentation in transrectal ultrasound (TRUS) is a challenging problem
due to the low contrast of TRUS images and the presence of imaging artifacts such as …
due to the low contrast of TRUS images and the presence of imaging artifacts such as …
Automatic coarse-to-refinement-based ultrasound prostate segmentation using optimal polyline segment tracking method and deep learning
Automatic segmentation of the prostate in transrectal ultrasound (TRUS) images provides
useful information for prostate cancer diagnosis and treatment. However, boundaries …
useful information for prostate cancer diagnosis and treatment. However, boundaries …
[HTML][HTML] An improved Yolov5s based on transformer backbone network for detection and classification of bronchoalveolar lavage cells
Biological tissue information of the lung, such as cells and proteins, can be obtained from
bronchoalveolar lavage fluid (BALF), through which it can be used as a complement to lung …
bronchoalveolar lavage fluid (BALF), through which it can be used as a complement to lung …
Classification of chest X-ray images by incorporation of medical domain knowledge into operation branch networks
T Tsuji, Y Hirata, K Kusunose, M Sata, S Kumagai… - BMC Medical …, 2023 - Springer
Background This study was conducted to alleviate a common difficulty in chest X-ray image
diagnosis: The attention region in a convolutional neural network (CNN) does not often …
diagnosis: The attention region in a convolutional neural network (CNN) does not often …
Bibliometric analysis of the global scientific production on machine learning applied to different cancer types
MA Ruiz-Fresneda, A Gijón… - Environmental Science and …, 2023 - Springer
Cancer disease is one of the main causes of death in the world, with million annual cases in
the last decades. The need to find a cure has stimulated the search for efficient treatments …
the last decades. The need to find a cure has stimulated the search for efficient treatments …
A robust and explainable structure-based algorithm for detecting the organ boundary from ultrasound multi-datasets
T Peng, Y Gu, J Zhang, Y Dong, G Di, W Wang… - Journal of Digital …, 2023 - Springer
Detecting the organ boundary in an ultrasound image is challenging because of the poor
contrast of ultrasound images and the existence of imaging artifacts. In this study, we …
contrast of ultrasound images and the existence of imaging artifacts. In this study, we …