PyDicer: An open-source python']python library for conversion and analysis of radiotherapy DICOM data

被引：0
|
作者：
Chlap, Phillip [1 ,2 ,3 ,7 ]
Al Mouiee, Daniel [1 ,2 ,3 ]
Finnegan, Robert N. [4 ,5 ]
Cui, Janet [2 ,8 ]
Chin, Vicky [1 ,2 ,3 ,6 ]
Deshpande, Shrikant [1 ,2 ,3 ]
Holloway, Lois [1 ,2 ,3 ,5 ]
机构：
[1] Univ New South Wales, South Western Sydney Clin Sch, Sydney, Australia
[2] Ingham Inst Appl Med Res, Sydney, Australia
[3] Liverpool & Macarthur Canc Therapy Ctr, Dept Radiat Oncol, Sydney, Australia
[4] Royal North Shore Hosp, Sydney, Australia
[5] Univ Sydney, Inst Med Phys, Sydney, Australia
[6] Univ Sydney, Image X Inst, Sydney, Australia
[7] Radformation Inc, New York, NY 10016 USA
[8] Microsoft, Sydney, Australia
来源：
SOFTWAREX | 2025年 / 29卷
关键词：
Radiotherapy; Medical image analysis; DICOM; NIfTI; Radiomics; Auto-segmentation;
D O I：
10.1016/j.softx.2024.102010
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
The organisation, conversion, cleaning and processing of DICOM data is an ongoing challenge across medical image analysis research projects. PyDicer (PYthon Dicom Image ConvertER) was created as a generalisable tool for use across a variety of radiotherapy research projects. This includes the conversion of DICOM objects into a standardised form as well as functionality to visualise, clean and analyse the converted data. The generalisability of PyDicer has been demonstrated by its use across a range of projects including the analysis of radiotherapy dose metrics and radiomics features as well as auto-segmentation training, inference and validation.
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收藏
页数：8
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