Literature DB >> 31946624

A Client/Server based Online Environment for the Calculation of Medical Segmentation Scores.

Maximilian Weber, Daniel Wild, Jurgen Wallner, Jan Egger.   

Abstract

Image segmentation plays a major role in medical imaging. Especially in radiology, the detection and development of tumors and other diseases can be supported by image segmentation applications. Tools that provide image segmentation and calculation of segmentation scores are not available at any time for every device due to the size and scope of functionalities they offer. These tools need huge periodic updates and do not properly work on old or weak systems. However, medical use-cases often require fast and accurate results. A complex and slow software can lead to additional stress and thus unnecessary errors. The aim of this contribution is the development of a cross-platform tool for medical segmentation use-cases. The goal is a device-independent and always available possibility for medical imaging including manual segmentation and metric calculation. The result is Studierfenster (studierfenster.at), a web-tool for manual segmentation and segmentation metric calculation. In this contribution, the focus lies on the segmentation metric calculation part of the tool. It provides the functionalities of calculating directed and undirected Hausdorff Distance (HD) and Dice Similarity Coefficient (DSC) scores for two uploaded volumes, filtering for specific values, searching for specific values in the calculated metrics and exporting filtered metric lists in different file formats.

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Year:  2019        PMID: 31946624     DOI: 10.1109/EMBC.2019.8856481

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  4 in total

1.  Deep learning-a first meta-survey of selected reviews across scientific disciplines, their commonalities, challenges and research impact.

Authors:  Jan Egger; Antonio Pepe; Christina Gsaxner; Yuan Jin; Jianning Li; Roman Kern
Journal:  PeerJ Comput Sci       Date:  2021-11-17

2.  Deep Learning Predicts the Malignant-Transformation-Free Survival of Oral Potentially Malignant Disorders.

Authors:  John Adeoye; Mohamad Koohi-Moghadam; Anthony Wing Ip Lo; Raymond King-Yin Tsang; Velda Ling Yu Chow; Li-Wu Zheng; Siu-Wai Choi; Peter Thomson; Yu-Xiong Su
Journal:  Cancers (Basel)       Date:  2021-12-01       Impact factor: 6.639

3.  Integrating the OHIF Viewer into XNAT: Achievements, Challenges and Prospects for Quantitative Imaging Studies.

Authors:  Simon J Doran; Mohammad Al Sa'd; James A Petts; James Darcy; Kate Alpert; Woonchan Cho; Lorena Escudero Sanchez; Sachidanand Alle; Ahmed El Harouni; Brad Genereaux; Erik Ziegler; Gordon J Harris; Eric O Aboagye; Evis Sala; Dow-Mu Koh; Dan Marcus
Journal:  Tomography       Date:  2022-02-11

4.  Studierfenster: an Open Science Cloud-Based Medical Imaging Analysis Platform.

Authors:  Jan Egger; Daniel Wild; Maximilian Weber; Christopher A Ramirez Bedoya; Florian Karner; Alexander Prutsch; Michael Schmied; Christina Dionysio; Dominik Krobath; Yuan Jin; Christina Gsaxner; Jianning Li; Antonio Pepe
Journal:  J Digit Imaging       Date:  2022-01-21       Impact factor: 4.056

  4 in total

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