Automatic extraction of imaging observation and assessment categories from breast magnetic resonance imaging reports with natural language processing
Abstract. Background:. Structured reports are not widely used and thus most reports exist in the form of free text. The process of data extraction by experts is time-consuming and error-prone, whereas data extraction by natural language processing (NLP) is a potential solution that could improve dia...
Main Authors: | Yi Liu, Li-Na Zhu, Qing Liu, Chao Han, Xiao-Dong Zhang, Xiao-Ying Wang, Peng Lyu |
---|---|
Format: | Article |
Language: | English |
Published: |
Wolters Kluwer
2019-07-01
|
Series: | Chinese Medical Journal |
Online Access: | http://journals.lww.com/10.1097/CM9.0000000000000301 |
Similar Items
-
Subdividing BI-RADS category 4 breast lesions observed on magnetic resonance imaging: Is it feasible?
by: Almir Galvão Vieira Bitencourt
Published: (2016-06-01) -
The implementation of natural language processing to extract index lesions from breast magnetic resonance imaging reports
by: Yi Liu, et al.
Published: (2019-12-01) -
Automatic Classification of Magnetic Resonance Imaging Reports Using Natural Language Processing
by: Nai-Yuan Wu, et al.
Published: (2018) -
Automatic Segmentation of Magnetic Resonance Images of the Brain
by: Spence, Kirk V. N.
Published: (2005) -
Diagnostic Magnetic Resonance Imaging of the Breast
by: Fahrettin Kilic, et al.
Published: (2012-08-01)