Zobrazeno 1 - 10
of 944
pro vyhledávání: '"Medical image fusion"'
Autor:
Weixiong Zhong
Publikováno v:
Measurement: Sensors, Vol 33, Iss , Pp 101146- (2024)
With the rapid development of artificial intelligence and medical technology, sensor technology, as an important tool to obtain medical data, provides a wealth of physiological parameter information, but the traditional medical image fusion methods a
Externí odkaz:
https://doaj.org/article/9d24e87019fd4ce4bfc46607475785e2
Publikováno v:
IEEE Access, Vol 12, Pp 70851-70869 (2024)
Glioma is a kind of brain disease with high incidence, high recurrence rate, high mortality, and low cure rate. To obtain accurate diagnosis results of brain glioma, doctors need to manually compare the imaging results of different modalities many ti
Externí odkaz:
https://doaj.org/article/6a4e9512e4074d32b4ae2e816c85e07f
Autor:
Yifeng Peng, Haijun Deng
Publikováno v:
BMC Medical Imaging, Vol 24, Iss 1, Pp 1-11 (2024)
Abstract With the rapid development of medical imaging technology and computer technology, the medical imaging artificial intelligence of computer-aided diagnosis based on machine learning has become an important part of modern medical diagnosis. Wit
Externí odkaz:
https://doaj.org/article/78fee9dde57546f38df2bea585c42d82
Publikováno v:
Sensors, Vol 24, Iss 13, p 4056 (2024)
The fusion of multi-modal medical images has great significance for comprehensive diagnosis and treatment. However, the large differences between the various modalities of medical images make multi-modal medical image fusion a great challenge. This p
Externí odkaz:
https://doaj.org/article/a773db6321434eb48a3c132b34110f3f
Publikováno v:
Sensors, Vol 24, Iss 11, p 3545 (2024)
Multi-modal medical image fusion (MMIF) is crucial for disease diagnosis and treatment because the images reconstructed from signals collected by different sensors can provide complementary information. In recent years, deep learning (DL) based metho
Externí odkaz:
https://doaj.org/article/f101a5a5278041a4929846c5bb3d591f
Publikováno v:
Journal of King Saud University: Computer and Information Sciences, Vol 35, Iss 8, Pp 101733- (2023)
Medical imaging has been widely used to diagnose various disorders over the past 20 years. Primary challenges in medicine include accurate disease identification and improved therapies. It is challenging for the medical experts to diagnose diseases u
Externí odkaz:
https://doaj.org/article/96d2ef08320b48f69c85714990d2fbbd
Publikováno v:
IEEE Access, Vol 11, Pp 43089-43100 (2023)
The prostate tissue structure is complex, the shape and size change is relatively large, and the surrounding anatomical structure is complex, so the task of segmenting prostate and prostate cancer is somewhat challenging. In this paper, the idea of d
Externí odkaz:
https://doaj.org/article/6e4f730f04654060bb07f7198923935a
Autor:
Jinu Sebastian, G.R. Gnana King
Publikováno v:
International Journal of Electronics and Telecommunications, Vol vol. 68, Iss No 4, Pp 867-873 (2022)
Nowadays, Medical imaging modalities like Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), Single Photon Emission Tomography (SPECT), and Computed Tomography (CT) play a crucial role in clinical diagnosis and treatment planning.
Externí odkaz:
https://doaj.org/article/faa8ab7a95244d5d8a12c55082291231
Publikováno v:
BMC Bioinformatics, Vol 23, Iss 1, Pp 1-32 (2022)
Abstract Background Today’s biomedical imaging technology has been able to present the morphological structure or functional metabolic information of organisms at different scale levels, such as organ, tissue, cell, molecule and gene. However, diff
Externí odkaz:
https://doaj.org/article/209c62e059a445f4b98cf989881f2e4b
Publikováno v:
Heliyon, Vol 9, Iss 6, Pp e17334- (2023)
For the past 25 years, medical imaging has been extensively used for clinical diagnosis. The main difficulties in medicine are accurate disease recognition and improved therapy. Using a single imaging modality to diagnose disease is challenging for c
Externí odkaz:
https://doaj.org/article/f33440779c11494cad9eea3981771c82