Radiomics and Multiomics Research

Di Dong; Shengyuan Liu; Zhenyu Liu; Wei Mu; Shuo Wang; Lizhi Shao; Bao Li; Jingwei Wei; Yuming Jiang; Xiangbo Wan; Jie Tian

doi:10.1007/978-981-99-8441-1_4

Radiomics and Multiomics Research

Di Dong
, Shengyuan Liu
, Zhenyu Liu
, Wei Mu
, Shuo Wang
, Lizhi Shao
, Bao Li
, Jingwei Wei
, Yuming Jiang
, Xiangbo Wan
, Jie Tian^*

^*Corresponding author for this work

CAS - Institute of Automation
Beihang University
Southern Medical University
Zhengzhou University First Affiliated Hospital

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

3 Scopus citations

Abstract

Medical imaging is a non-invasive diagnostic method that is commonly used in clinical practice, and its role has gradually evolved from a major diagnostic tool to an important means to assist doctors in personalized and precise treatment. At present, clinicians rely on subjective experience to make diagnoses based on qualitative signs such as the size, shape, location, and density of lesions in images. However, the number of these qualitative signs is limited, and it is difficult to fully reflect the characteristics of a patient’s disease in these images. With the development of artificial intelligence and the increase in medical imaging data, medical image analysis research has grown [1].

Original language	English
Title of host publication	Artificial Intelligence in Medical Imaging in China
Publisher	Springer Nature
Pages	61-83
Number of pages	23
ISBN (Electronic)	9789819984411
ISBN (Print)	9789819984404
DOIs	https://doi.org/10.1007/978-981-99-8441-1_4
State	Published - 1 Jan 2024
Externally published	Yes

Access to Document

10.1007/978-981-99-8441-1_4

Cite this

@inbook{3d5bcbc364ad432a86deaeaa872d1cba,

title = "Radiomics and Multiomics Research",

abstract = "Medical imaging is a non-invasive diagnostic method that is commonly used in clinical practice, and its role has gradually evolved from a major diagnostic tool to an important means to assist doctors in personalized and precise treatment. At present, clinicians rely on subjective experience to make diagnoses based on qualitative signs such as the size, shape, location, and density of lesions in images. However, the number of these qualitative signs is limited, and it is difficult to fully reflect the characteristics of a patient{\textquoteright}s disease in these images. With the development of artificial intelligence and the increase in medical imaging data, medical image analysis research has grown [1].",

author = "Di Dong and Shengyuan Liu and Zhenyu Liu and Wei Mu and Shuo Wang and Lizhi Shao and Bao Li and Jingwei Wei and Yuming Jiang and Xiangbo Wan and Jie Tian",

note = "Publisher Copyright: {\textcopyright} People{\textquoteright}s Medical Publishing House, PR of China 2024.",

year = "2024",

month = jan,

day = "1",

doi = "10.1007/978-981-99-8441-1\_4",

language = "英语",

isbn = "9789819984404",

pages = "61--83",

booktitle = "Artificial Intelligence in Medical Imaging in China",

publisher = "Springer Nature",

}

TY - CHAP

T1 - Radiomics and Multiomics Research

AU - Dong, Di

AU - Liu, Shengyuan

AU - Liu, Zhenyu

AU - Mu, Wei

AU - Wang, Shuo

AU - Shao, Lizhi

AU - Li, Bao

AU - Wei, Jingwei

AU - Jiang, Yuming

AU - Wan, Xiangbo

AU - Tian, Jie

PY - 2024/1/1

Y1 - 2024/1/1

N2 - Medical imaging is a non-invasive diagnostic method that is commonly used in clinical practice, and its role has gradually evolved from a major diagnostic tool to an important means to assist doctors in personalized and precise treatment. At present, clinicians rely on subjective experience to make diagnoses based on qualitative signs such as the size, shape, location, and density of lesions in images. However, the number of these qualitative signs is limited, and it is difficult to fully reflect the characteristics of a patient’s disease in these images. With the development of artificial intelligence and the increase in medical imaging data, medical image analysis research has grown [1].

AB - Medical imaging is a non-invasive diagnostic method that is commonly used in clinical practice, and its role has gradually evolved from a major diagnostic tool to an important means to assist doctors in personalized and precise treatment. At present, clinicians rely on subjective experience to make diagnoses based on qualitative signs such as the size, shape, location, and density of lesions in images. However, the number of these qualitative signs is limited, and it is difficult to fully reflect the characteristics of a patient’s disease in these images. With the development of artificial intelligence and the increase in medical imaging data, medical image analysis research has grown [1].

UR - https://www.scopus.com/pages/publications/105002529723

U2 - 10.1007/978-981-99-8441-1_4

DO - 10.1007/978-981-99-8441-1_4

M3 - 章节

AN - SCOPUS:105002529723

SN - 9789819984404

SP - 61

EP - 83

BT - Artificial Intelligence in Medical Imaging in China

PB - Springer Nature

ER -

Radiomics and Multiomics Research

Abstract

Access to Document

Other files and links

Fingerprint

Cite this