KneeBones3Dify: Open-source software for segmentation and 3D reconstruction of knee bones from MRI data

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX Pub Date : 2024-08-22 DOI:10.1016/j.softx.2024.101854

Lucia Maddalena , Diego Romano , Francesco Gregoretti , Gianluca De Lucia , Laura Antonelli , Ernesto Soscia , Gabriele Pontillo , Carla Langella , Flavio Fazioli , Carla Giusti , Rosario Varriale

{"title":"KneeBones3Dify: Open-source software for segmentation and 3D reconstruction of knee bones from MRI data","authors":"Lucia Maddalena , Diego Romano , Francesco Gregoretti , Gianluca De Lucia , Laura Antonelli , Ernesto Soscia , Gabriele Pontillo , Carla Langella , Flavio Fazioli , Carla Giusti , Rosario Varriale","doi":"10.1016/j.softx.2024.101854","DOIUrl":null,"url":null,"abstract":"<div><p>KneeBones3Dify is a Python software tool that supports detailed analysis of knee pathologies and preoperative planning for knee replacement surgery based on patient-specific 3D models. It produces printable 3D bones in a stereolithography file format by automatically segmenting the femur, patella, and tibia from high-resolution Magnetic Resonance (MR) images with nearly isotropic voxel dimensions. Our software avoids time-consuming and subjective manual segmentation by specialists, offering an accurate and efficient alternative employing GPU acceleration. We validated the results by computing objective metrics against the ground truth voxel-wise segmentation produced for a 3D MR image by specialists, who also confirmed the reconstruction accuracy qualitatively. KneeBones3Dify and annotated data are publicly available, enabling broader research and clinical practice use.</p></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"27 ","pages":"Article 101854"},"PeriodicalIF":2.4000,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352711024002255/pdfft?md5=f20dcefe678f0f6669dd86b85a8ecb3b&pid=1-s2.0-S2352711024002255-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SoftwareX","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352711024002255","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}

引用次数: 0

Abstract

KneeBones3Dify is a Python software tool that supports detailed analysis of knee pathologies and preoperative planning for knee replacement surgery based on patient-specific 3D models. It produces printable 3D bones in a stereolithography file format by automatically segmenting the femur, patella, and tibia from high-resolution Magnetic Resonance (MR) images with nearly isotropic voxel dimensions. Our software avoids time-consuming and subjective manual segmentation by specialists, offering an accurate and efficient alternative employing GPU acceleration. We validated the results by computing objective metrics against the ground truth voxel-wise segmentation produced for a 3D MR image by specialists, who also confirmed the reconstruction accuracy qualitatively. KneeBones3Dify and annotated data are publicly available, enabling broader research and clinical practice use.

查看原文本刊更多论文

KneeBones3Dify：根据核磁共振成像数据对膝关节骨骼进行分割和三维重建的开源软件

KneeBones3Dify 是一款 Python 软件工具，可支持膝关节病理的详细分析，并根据患者特定的三维模型制定膝关节置换手术的术前计划。它通过从高分辨率磁共振（MR）图像中自动分割股骨、髌骨和胫骨，以近乎各向同性的体素尺寸，生成可打印的立体光刻文件格式的三维骨骼。我们的软件避免了专家耗时且主观的手动分割，提供了一种采用 GPU 加速的准确高效的替代方法。我们根据专家为三维核磁共振图像制作的真实体素分割计算客观指标，验证了结果，专家也定性地确认了重建的准确性。KneeBones3Dify和注释数据均可公开获取，从而可用于更广泛的研究和临床实践。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

SoftwareX COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

5.50

自引率

2.90%

发文量

184

审稿时长

9 weeks

期刊介绍： SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.