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

被引：2

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.

引用

页数：8

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