A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
AnatomySketch : An Extensible Open-Source Software Platform for Medical Image Analysis Algorithm Development (2022)
Zhuang, M., Chen, Z., Wang, H., Tang, H., He, J., Qin, B., Yang, Y., Jin, X., Yu, M., Jin, B., Li, T., & Kettunen, L. (2022). AnatomySketch : An Extensible Open-Source Software Platform for Medical Image Analysis Algorithm Development. Journal of Digital Imaging, 35(6), 1623-1633. https://doi.org/10.1007/s10278-022-00660-5
JYU-tekijät tai -toimittajat
Julkaisun tiedot
Julkaisun kaikki tekijät tai toimittajat: Zhuang, Mingrui; Chen, Zhonghua; Wang, Hongkai; Tang, Hong; He, Jiang; Qin, Bobo; Yang, Yuxin; Jin, Xiaoxian; Yu, Mengzhu; Jin, Baitao; et al.
Lehti tai sarja: Journal of Digital Imaging
ISSN: 0897-1889
eISSN: 1618-727X
Julkaisuvuosi: 2022
Ilmestymispäivä: 29.06.2022
Volyymi: 35
Lehden numero: 6
Artikkelin sivunumerot: 1623-1633
Kustantaja: Springer
Julkaisumaa: Yhdysvallat (USA)
Julkaisun kieli: englanti
DOI: https://doi.org/10.1007/s10278-022-00660-5
Julkaisun avoin saatavuus: Avoimesti saatavilla
Julkaisukanavan avoin saatavuus: Osittain avoin julkaisukanava
Julkaisu on rinnakkaistallennettu (JYX): https://jyx.jyu.fi/handle/123456789/82356
Tiivistelmä
The development of medical image analysis algorithm is a complex process including the multiple sub-steps of model training, data visualization, human–computer interaction and graphical user interface (GUI) construction. To accelerate the development process, algorithm developers need a software tool to assist with all the sub-steps so that they can focus on the core function implementation. Especially, for the development of deep learning (DL) algorithms, a software tool supporting training data annotation and GUI construction is highly desired. In this work, we constructed AnatomySketch, an extensible open-source software platform with a friendly GUI and a flexible plugin interface for integrating user-developed algorithm modules. Through the plugin interface, algorithm developers can quickly create a GUI-based software prototype for clinical validation. AnatomySketch supports image annotation using the stylus and multi-touch screen. It also provides efficient tools to facilitate the collaboration between human experts and artificial intelligent (AI) algorithms. We demonstrate four exemplar applications including customized MRI image diagnosis, interactive lung lobe segmentation, human-AI collaborated spine disc segmentation and Annotation-by-iterative-Deep-Learning (AID) for DL model training. Using AnatomySketch, the gap between laboratory prototyping and clinical testing is bridged and the development of MIA algorithms is accelerated. The software is opened at https://github.com/DlutMedimgGroup/AnatomySketch-Software.
YSO-asiasanat: kuva-analyysi; visualisointi; lääketiede; tietokoneohjelmat; algoritmit; ohjelmointi; tekoäly; ihminen-konejärjestelmät; ihmisen ja tietokoneen vuorovaikutus; koneoppiminen; syväoppiminen
Vapaat asiasanat: medical image analysis; image annotation; user interaction; algorithm development; deep learning; AnatomySketch
Liittyvät organisaatiot
OKM-raportointi: Kyllä
Raportointivuosi: 2022
JUFO-taso: 1
