Zobrazeno 1 - 10
of 2 741
pro vyhledávání: '"biomedical image"'
Autor:
Niloy Sikder, Md. Al-Masrur Khan, Anupam Kumar Bairagi, Mehedi Masud, Jun Jiat Tiang, Abdullah-Al Nahid
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Viruses are submicroscopic agents that can infect other lifeforms and use their hosts’ cells to replicate themselves. Despite having simplistic genetic structures among all living beings, viruses are highly adaptable, resilient, and capabl
Externí odkaz:
https://doaj.org/article/fd9fe3de90924bf8814e26e582672fdf
Publikováno v:
Frontiers in Signal Processing, Vol 4 (2024)
Externí odkaz:
https://doaj.org/article/4209acbb23f94a0f92f88aa96b9b7647
Autor:
Sarah A. Alzakari, Mashael Maashi, Saad Alahmari, Munya A. Arasi, Abeer A. K. Alharbi, Ahmed Sayed
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)
Abstract Laryngeal cancer exhibits a notable global health burden, with later-stage detection contributing to a low mortality rate. Laryngeal cancer diagnosis on throat region images is a pivotal application of computer vision (CV) and medical image
Externí odkaz:
https://doaj.org/article/4d3d2853dec14b0fa53d4660a687ea46
Autor:
Amal Alshardan, Hany Mahgoub, Nuha Alruwais, Abdulbasit A. Darem, Wafa Sulaiman Almukadi, Abdullah Mohamed
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract Inverse problems in biomedical image analysis represent a significant frontier in disease detection, leveraging computational methodologies and mathematical modelling to unravel complex data embedded within medical images. These problems inc
Externí odkaz:
https://doaj.org/article/926e6ba3080e424494808fc31ef527c1
Publikováno v:
Journal of Pathology Informatics, Vol 15, Iss , Pp 100390- (2024)
Cytomorphology evaluation of bone marrow cell is the initial step to diagnose different hematological diseases. This assessment is still manually performed by trained specialists, who may be a bottleneck within the clinical process. Deep learning alg
Externí odkaz:
https://doaj.org/article/38685f3df52a4fb2a64f035d77c7d936
Publikováno v:
Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki, Vol 22, Iss 3, Pp 84-92 (2024)
Biomedical image segmentation plays an important role in quantitative analysis, clinical diagnosis, and medical manipulation. Objects in medical images have different scales, types, complex backgrounds, and similar tissue appearances, making informat
Externí odkaz:
https://doaj.org/article/e9c3cec8b5c744a083e2d8d157e4f389
Publikováno v:
Applied Computer Systems, Vol 29, Iss 1, Pp 35-44 (2024)
Urine sediment examination (USE) is an essential aspect in detecting urinary system diseases, and it is a prerequisite for diagnostic procedures. Urine images are complex, containing numerous particles, which makes a detailed analysis and interpretat
Externí odkaz:
https://doaj.org/article/69560405c4494d7295a435087c9f81e4
Autor:
Arindam Halder, Sanghita Gharami, Priyangshu Sadhu, Pawan Kumar Singh, Marcin Woźniak, Muhammad Fazal Ijaz
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)
Abstract In recent years, the growth spurt of medical imaging data has led to the development of various machine learning algorithms for various healthcare applications. The MedMNISTv2 dataset, a comprehensive benchmark for 2D biomedical image classi
Externí odkaz:
https://doaj.org/article/9bff8f1bf80d482bae8c98135b2b2caf
Autor:
Zheng Wang, Xinyu Tan, Yang Xue, Chen Xiao, Kejuan Yue, Kaibin Lin, Chong Wang, Qiuhong Zhou, Jianglin Zhang
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract Current assessment methods for diabetic foot ulcers (DFUs) lack objectivity and consistency, posing a significant risk to diabetes patients, including the potential for amputations, highlighting the urgent need for improved diagnostic tools
Externí odkaz:
https://doaj.org/article/25373eb3724b4c0aa2a1c061551e6c6b
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 36, Iss 7, Pp 102130- (2024)
Accurate diagnosis of kidney disease is crucial, as it is a significant health concern that demands precise identification for effective and appropriate treatment. Deep learning methods are increasingly recognized as valuable tools for disease diagno
Externí odkaz:
https://doaj.org/article/9279494aea0545379df031eeb2f2e5e9