Zobrazeno 1 - 10
of 99 884
pro vyhledávání: '"Texture Features"'
Autor:
Zhang, Ruojie1,2 (AUTHOR) ruojie_gogo@163.com, Shen, Yilang1 (AUTHOR) shenylang@mail.sysu.edu.cn
Publikováno v:
Remote Sensing. Oct2024, Vol. 16 Issue 20, p3862. 21p.
Autor:
Qiu, Xin1 qiuxinfrank@163.com, Zhu, Tianfeng1, Zhao, Zhenhui1,2, Cui, Zhiwen1,3, Deng, Hansheng1,4,5, Tang, Shengping1 tangshengping56@126.com, Sechi, Leonardo Antonio5 sechila@uniss.it, Caggiari, Gianfilippo4 gianfilippocaggiari@gmail.com, Zhao, Cailei1 zhaocailei197866@163.com, Xiong, Zhu1 bamboobear@163.com
Publikováno v:
Journal of Orthopaedic Surgery & Research. 6/20/2024, Vol. 19 Issue 1, p1-10. 10p.
Autor:
Xin Qiu, Tianfeng Zhu, Zhenhui Zhao, Zhiwen Cui, Hansheng Deng, Shengping Tang, Leonardo Antonio Sechi, Gianfilippo Caggiari, Cailei Zhao, Zhu Xiong
Publikováno v:
Journal of Orthopaedic Surgery and Research, Vol 19, Iss 1, Pp 1-10 (2024)
Abstract Objectives To develop an objective method based on texture analysis on MRI for diagnosis of congenital muscular torticollis (CMT). Material and methods The T1- and T2-weighted imaging, Q-dixon, and T1-mapping MRI data of 38 children with CMT
Externí odkaz:
https://doaj.org/article/899044f33c204708971a649d37db514f
Akademický článek
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Akademický článek
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Autor:
Davidson, Andrew, Morley-Bunker, Arthur, Wiggins, George, Walker, Logan, Harris, Gavin, Mukundan, Ramakrishnan, Investigators, kConFab
Chromogenic RNAscope dye and haematoxylin staining of cancer tissue facilitates diagnosis of the cancer type and subsequent treatment, and fits well into existing pathology workflows. However, manual quantification of the RNAscope transcripts (dots),
Externí odkaz:
http://arxiv.org/abs/2401.15886
Publikováno v:
BMC Medical Imaging, Vol 24, Iss 1, Pp 1-22 (2024)
Abstract Background Cancer pathology shows disease development and associated molecular features. It provides extensive phenotypic information that is cancer-predictive and has potential implications for planning treatment. Based on the exceptional p
Externí odkaz:
https://doaj.org/article/f9c12945bb2e4f9fa3b22bad8f966471
Autor:
Fan, Jiahui1 (AUTHOR) 202221051094@mail.bnu.edu.cn, Yao, Yunjun1 (AUTHOR) yaoyunjun@bnu.edu.cn, Tang, Qingxin2 (AUTHOR) tangqingxin@lcu.edu.cn, Zhang, Xueyi3 (AUTHOR) 202231051059@mail.bnu.edu.cn, Xu, Jia4 (AUTHOR) jiax5@student.unimelb.edu.au, Yu, Ruiyang1 (AUTHOR) liululu@mail.bnu.edu.cn, Liu, Lu1 (AUTHOR) xiezijing@mail.bnu.edu.cn, Xie, Zijing1 (AUTHOR) njing@mail.bnu.edu.cn, Ning, Jing1 (AUTHOR) 202321051212@mail.bnu.edu.cn, Zhang, Luna1 (AUTHOR)
Publikováno v:
Remote Sensing. May2024, Vol. 16 Issue 9, p1539. 20p.
Publikováno v:
Machine Learning in Medical Imaging (MLMI) 2023
Multi-class colorectal tissue classification is a challenging problem that is typically addressed in a setting, where it is assumed that ample amounts of training data is available. However, manual annotation of fine-grained colorectal tissue samples
Externí odkaz:
http://arxiv.org/abs/2401.01164