Advanced medical image segmentation enhancement: a particle-swarm-optimization-based histogram equalization approach
S Saifullah, R Dreżewski - Applied Sciences, 2024 - mdpi.com
Accurate medical image segmentation is paramount for precise diagnosis and treatment in
modern healthcare. This research presents a comprehensive study of the efficacy of particle …
modern healthcare. This research presents a comprehensive study of the efficacy of particle …
COVSeg‐NET: A deep convolution neural network for COVID‐19 lung CT image segmentation
XQ Zhang, GY Wang, SG Zhao - International Journal of …, 2021 - Wiley Online Library
COVID‐19 is a new type of respiratory infectious disease that poses a serious threat to the
survival of human beings all over the world. Using artificial intelligence technology to …
survival of human beings all over the world. Using artificial intelligence technology to …
Tumor segmentation via enhanced area growth algorithm for lung CT images
A Khorshidi - BMC Medical Imaging, 2023 - Springer
Background Since lung tumors are in dynamic conditions, the study of tumor growth and its
changes is of great importance in primary diagnosis. Methods Enhanced area growth (EAG) …
changes is of great importance in primary diagnosis. Methods Enhanced area growth (EAG) …
Research on CT Lung Segmentation Method of Preschool Children based on Traditional Image Processing and ResUnet
Lung segmentation using computed tomography (CT) images is important for diagnosing
various lung diseases. Currently, no lung segmentation method has been developed for …
various lung diseases. Currently, no lung segmentation method has been developed for …
P2P-COVID-GAN: Classification and segmentation of COVID-19 lung infections from CT images using GAN
Early and automatic segmentation of lung infections from computed tomography images of
COVID-19 patients is crucial for timely quarantine and effective treatment. However …
COVID-19 patients is crucial for timely quarantine and effective treatment. However …
A deep adversarial model for segmentation-assisted COVID-19 diagnosis using CT images
H Yao, W Wan, X Li - EURASIP Journal on Advances in Signal Processing, 2022 - Springer
The outbreak of coronavirus disease 2019 (COVID-19) is spreading rapidly around the
world, resulting in a global pandemic. Imaging techniques such as computed tomography …
world, resulting in a global pandemic. Imaging techniques such as computed tomography …
Current Diagnostic Techniques for Pneumonia: A Scoping Review
Community-acquired pneumonia is one of the most lethal infectious diseases, especially for
infants and the elderly. Given the variety of causative agents, the accurate early detection of …
infants and the elderly. Given the variety of causative agents, the accurate early detection of …
An efficient CNN-based hybrid classification and segmentation approach for COVID-19 detection.
COVID-19 remains to proliferate precipitously in the world. It has significantly influenced
public health, the world economy, and the persons' lives. Hence, there is a need to speed up …
public health, the world economy, and the persons' lives. Hence, there is a need to speed up …
Lung infection region quantification, recognition, and virtual reality rendering of CT scan of COVID-19
In recent years, virtual reality has experienced steady growth in the medical field, such as
surgery, rehabilitation, disease diagnostic, and learning. The 3D representation of …
surgery, rehabilitation, disease diagnostic, and learning. The 3D representation of …
Classification performance for COVID patient prognosis from automatic AI segmentation—a single-center study
Background: COVID assessment can be performed using the recently developed individual
risk score (prediction of severe respiratory failure in hospitalized patients with SARS-COV2 …
risk score (prediction of severe respiratory failure in hospitalized patients with SARS-COV2 …