Zobrazeno 1 - 10
of 215
pro vyhledávání: '"pathological images"'
Publikováno v:
Journal of Translational Medicine, Vol 22, Iss 1, Pp 1-18 (2024)
Abstract Background During the prolonged period from Human Papillomavirus (HPV) infection to cervical cancer development, Low-Grade Squamous Intraepithelial Lesion (LSIL) stage provides a critical opportunity for cervical cancer prevention, giving th
Externí odkaz:
https://doaj.org/article/0dd669bc28004a18a9bb7f8ac9d6af49
Autor:
Cong Li, Shuanlong Che, Haotian Gong, Youde Ding, Yizhou Luo, Jianing Xi, Ling Qi, Guiying Zhang
Publikováno v:
Frontiers in Oncology, Vol 14 (2024)
Externí odkaz:
https://doaj.org/article/428403cb5bf7421c977ee34dd7c282fb
Autor:
Cong Li, Shuanlong Che, Haotian Gong, Youde Ding, Yizhou Luo, Jianing Xi, Ling Qi, Guiying Zhang
Publikováno v:
Frontiers in Oncology, Vol 14 (2024)
Vessel density within tumor tissues strongly correlates with tumor proliferation and serves as a critical marker for tumor grading. Recognition of vessel density by pathologists is subject to a strong inter-rater bias, thus limiting its prognostic va
Externí odkaz:
https://doaj.org/article/bfa75d25669b4251ba34e00f6fb3086d
Publikováno v:
IEEE Access, Vol 12, Pp 155365-155378 (2024)
To address the burdensome and time-consuming nature of manual diagnosis of pathological sections, this study proposes an automated pathological image detection system. This system can directly detect pathological images and accurately locate lesion t
Externí odkaz:
https://doaj.org/article/37c8acf93b944941b21b582567f5cb16
Publikováno v:
Journal of Computing and Information Technology, Vol 32, Iss 2, Pp 127-142 (2024)
Multi-class classification of breast cancer pathological images remains challenging due to complex image features and limited datasets. This study proposes SSResNeXt, a novel deep learning architecture incorporating a new Small-SE-ResNeXt Block with
Externí odkaz:
https://doaj.org/article/b7a338a8130a49a7bf2aeaffeda2c678
Publikováno v:
IET Image Processing, Vol 18, Iss 1, Pp 175-193 (2024)
Abstract Artificial intelligence decision systems play an important supporting role in the field of medical information. Medical image analysis is an important part of decision systems and an even more important part of medical diagnosis and treatmen
Externí odkaz:
https://doaj.org/article/47aaff66aa704aa9b05546446d105358
Autor:
Abdelwahab Said Hassan, Anuradha Thakare, Manisha Bhende, K.D.V. Prasad, Pavitar Parkash Singh, Haewon Byeon
Publikováno v:
Measurement: Sensors, Vol 33, Iss , Pp 101211- (2024)
High-resolution pathological images play a pivotal role in accurate disease diagnosis and are important in precision medicine. However, obtaining real-time high-resolution images faces challenges due to hardware limitations and scanning time constrai
Externí odkaz:
https://doaj.org/article/498eafca96cf4f34b425f0fcebda9d42
Publikováno v:
Frontiers in Oncology, Vol 14 (2024)
IntroductionImmune infiltration within the tumor microenvironment (TME) plays a significant role in the onset and progression of hepatocellular carcinoma (HCC). Machine learning applied to pathological images offers a practical means to explore the T
Externí odkaz:
https://doaj.org/article/654819af55b1451b89252a51fd738f6e
Autor:
Hamed Zamanian, Ahmad Shalbaf
Publikováno v:
Frontiers in Biomedical Technologies, Vol 11, Iss 2 (2024)
Purpose: This study aims to diagnose the severity of important pathological indices, i.e., fibrosis, steatosis, lobular inflammation, and ballooning from the pathological images of the liver tissue based on extracted features by radiomics methods.
Externí odkaz:
https://doaj.org/article/625036f0810e4c1bb928794f5fce4959
Publikováno v:
Cancer Medicine, Vol 13, Iss 6, Pp n/a-n/a (2024)
Abstract Background Pseudomyxoma peritonei (PMP) is a rare clinical malignant syndrome, and its rarity causes a lack of pathology research. This study aims to quantitatively analyze HE‐stained pathological images (PIs), and develop a new predictive
Externí odkaz:
https://doaj.org/article/431f8eaa25d24124a79e5c746a4c0e04