Zobrazeno 1 - 10
of 315
pro vyhledávání: '"biomedical MRI"'
Publikováno v:
IET Image Processing, Vol 18, Iss 13, Pp 3892-3903 (2024)
Abstract Medical image registration is essential and a key step in many advanced medical image tasks. In recent years, medical image registration has been applied to many clinical diagnoses, but large deformation registration is still a challenge. De
Externí odkaz:
https://doaj.org/article/4c95a3d75d0c4510b758b0b3176295a4
Publikováno v:
IET Image Processing, Vol 18, Iss 12, Pp 3556-3569 (2024)
Abstract Cervical cancer is a major health concern, particularly in developing countries with limited medical resources. This study introduces two models aimed at improving cervical tumor segmentation: a semi‐automatic model that fine‐tunes the S
Externí odkaz:
https://doaj.org/article/784cab296e834dc4ac7fbdceda521417
Publikováno v:
IET Image Processing, Vol 18, Iss 6, Pp 1598-1612 (2024)
Abstract Whole brain segmentation from magnetic resonance images (MRI) is crucial in diagnosing brain diseases and analyzing neuroimaging data. Despite advances through deep learning, challenges such as uneven gray distribution and the presence of ar
Externí odkaz:
https://doaj.org/article/2ea3524e11bf4a40af6263804387fa0c
Autor:
JianFeng Li, YanMin Niu
Publikováno v:
IET Image Processing, Vol 18, Iss 5, Pp 1189-1199 (2024)
Abstract The fusion and utilization of multi‐scale deep and shallow features are of great significance in liver tumour segmentation. This study proposes a dual encoding DDS‐UNet liver tumour segmentation method based on multi‐scale deep and sha
Externí odkaz:
https://doaj.org/article/2830974307f84094b521b627d7968f8b
Autor:
Marzieh Ghahramani, Nabiollah Shiri
Publikováno v:
IET Image Processing, Vol 18, Iss 5, Pp 1358-1372 (2024)
Abstract An adaptive neuro‐fuzzy inference system is presented which is optimized by a genetic algorithm to classify normal and abnormal brain tumours. The classifier is fast and simple, named genetic algorithm‐adaptive neuro‐fuzzy inference sy
Externí odkaz:
https://doaj.org/article/8f7a726a8915424997e145e5f948956d
Publikováno v:
IET Image Processing, Vol 18, Iss 4, Pp 839-855 (2024)
Abstract Deep learning‐based image registration (DLIR) has been widely developed, but it remains challenging in perceiving small and large deformations. Besides, the effectiveness of the DLIR methods was also rarely validated on the downstream task
Externí odkaz:
https://doaj.org/article/1b2e06564c7245fcbfc7d52534e5cc62
Autor:
Xiaojie Li, Xin Fei, Zhe Yan, Hongping Ren, Canghong Shi, Xian Zhang, Imran Mumtaz, Yong Luo, Xi Wu
Publikováno v:
IET Computer Vision, Vol 18, Iss 1, Pp 1-14 (2024)
Abstract The Coronavirus Disease 2019 (COVID‐19) epidemic has constituted a Public Health Emergency of International Concern. Chest computed tomography (CT) can help early reveal abnormalities indicative of lung disease. Thus, accurate and automati
Externí odkaz:
https://doaj.org/article/5469ee21bf7a4e86b81763cc3ce89acc
Publikováno v:
IET Image Processing, Vol 17, Iss 10, Pp 3040-3054 (2023)
Abstract Due to the improvement in computing power and the development of computer technology, deep learning has pene‐trated into various fields of the medical industry. Segmenting lesion areas in medical scans can help clinicians make accurate dia
Externí odkaz:
https://doaj.org/article/87ad8283a2ee44ad9d580d7904486da9
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.