Zobrazeno 1 - 10
of 5 199
pro vyhledávání: '"Medical image segmentation"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract UNet architecture has achieved great success in medical image segmentation applications. However, these models still encounter several challenges. One is the loss of pixel-level information caused by multiple down-sampling steps. Additionall
Externí odkaz:
https://doaj.org/article/ff06928ac7a043fea32ee08b15754a2c
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract Computer-aided diagnosis has been slow to develop in the field of oral ulcers. One of the major reasons for this is the lack of publicly available datasets. However, oral ulcers have cancerous lesions and their mortality rate is high. The ab
Externí odkaz:
https://doaj.org/article/956681b70c984f20bd50bebb5188c528
Autor:
Huu Sy Le, Kha Tu Huynh
Publikováno v:
Vietnam Journal of Computer Science, Vol 11, Iss 03, Pp 377-410 (2024)
The paper proposes a robust and efficient model designed for multi-label abdominal organ segmentation, featuring a substantially reduced number of parameters. The model focuses on the effectiveness of edge guidance in segmentation and leverages a 3D-
Externí odkaz:
https://doaj.org/article/d0b500355b5247b2b19125982c6f966c
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Swin Transformer is an important work among all the attempts to reduce the computational complexity of Transformers while maintaining its excellent performance in computer vision. Window-based patch self-attention can use the local connectiv
Externí odkaz:
https://doaj.org/article/893dd2e769664270bf13bc620e761048
Autor:
Lai WEI, Menghan HU
Publikováno v:
Virtual Reality & Intelligent Hardware, Vol 6, Iss 3, Pp 181-202 (2024)
Deep learning has been extensively applied to medical image segmentation, resulting in significant advancements in the field of deep neural networks for medical image segmentation since the notable success of U-Net in 2015. However, the application o
Externí odkaz:
https://doaj.org/article/e010b2c58bfa49cdb6821eae468e3012
Publikováno v:
Chinese Journal of Magnetic Resonance, Vol 41, Iss 2, Pp 151-161 (2024)
The pancreas has always been one of the most challenging parts in medical image segmentation due to its complex anatomical structure and complex surrounding environment. Aiming at the above problems, a deep learning segmentation model combining dual
Externí odkaz:
https://doaj.org/article/e794eedfdfe241f093d879920ff7f02a
Publikováno v:
Jisuanji kexue yu tansuo, Vol 18, Iss 6, Pp 1383-1403 (2024)
U-Net and its variants have showcased exceptional performance in the domain of breast medical image segmentation. By employing a fully convolutional network (FCN) structure for semantic segmentation, the symmetrical structure of U-Net offers remarkab
Externí odkaz:
https://doaj.org/article/c3a69497d88f40d29926b0eeab2f4c2f
Publikováno v:
BMC Oral Health, Vol 24, Iss 1, Pp 1-17 (2024)
Abstract Background Oral mucosal diseases are similar to the surrounding normal tissues, i.e., their many non-salient features, which poses a challenge for accurate segmentation lesions. Additionally, high-precision large models generate too many par
Externí odkaz:
https://doaj.org/article/3a9aa74498db424bbca60891a9327cb4
Publikováno v:
BioMedical Engineering OnLine, Vol 23, Iss 1, Pp 1-14 (2024)
Abstract Background Congenital heart disease (CHD) is one of the most common birth defects in the world. It is the leading cause of infant mortality, necessitating an early diagnosis for timely intervention. Prenatal screening using ultrasound is the
Externí odkaz:
https://doaj.org/article/336b9153e1954cd0825b32b902b7151d
Publikováno v:
Frontiers in Neurology, Vol 15 (2024)
ObjectiveThe primary aim of this investigation was to devise an intelligent approach for interpreting and measuring the spatial orientation of semicircular canals based on cranial MRI. The ultimate objective is to employ this intelligent method to co
Externí odkaz:
https://doaj.org/article/ca329641b12b46b0ad37df0be536b6a2