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Two-dimensional segmentation fusion tool: an extensible, free-to-use, user-friendly tool for combining different bidimensional segmentations.
Piccinini, Filippo; Drudi, Lorenzo; Pyun, Jae-Chul; Lee, Misu; Kwak, Bongseop; Ku, Bosung; Carbonaro, Antonella; Martinelli, Giovanni; Castellani, Gastone.
Afiliación
  • Piccinini F; IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy.
  • Drudi L; Department of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy.
  • Pyun JC; Student, Computer Science and Engineering, University of Bologna, Bologna, Italy.
  • Lee M; Department of Materials Science and Engineering, Yonsei University, Seoul, Republic of Korea.
  • Kwak B; Division of Life Sciences, College of Life Science and Bioengineering, Incheon National University, Incheon, Republic of Korea.
  • Ku B; Institute for New Drug Development, College of Life Science and Bioengineering, Incheon National University, Incheon, Republic of Korea.
  • Carbonaro A; College of Medicine, Dongguk University, Goyang-si, Gyeonggi-do, Republic of Korea.
  • Martinelli G; Central R&D Center, Medical and Bio Decision (MBD) Co., Ltd., Suwon, Republic of Korea.
  • Castellani G; Department of Computer Science and Engineering (DISI), University of Bologna, Cesena, Italy.
Front Bioeng Biotechnol ; 12: 1339723, 2024.
Article en En | MEDLINE | ID: mdl-38357706
ABSTRACT

Introduction:

In several fields, the process of fusing multiple two-dimensional (2D) closed lines is an important step. For instance, this is fundamental in histology and oncology in general. The treatment of a tumor consists of numerous steps and activities. Among them, segmenting the cancer area, that is, the correct identification of its spatial location by the segmentation technique, is one of the most important and at the same time complex and delicate steps. The difficulty in deriving reliable segmentations stems from the lack of a standard for identifying the edges and surrounding tissues of the tumor area. For this reason, the entire process is affected by considerable subjectivity. Given a tumor image, different practitioners can associate different segmentations with it, and the diagnoses produced may differ. Moreover, experimental data show that the analysis of the same area by the same physician at two separate timepoints may result in different lines being produced. Accordingly, it is challenging to establish which contour line is the ground truth.

Methods:

Starting from multiple segmentations related to the same tumor, statistical metrics and computational procedures could be exploited to combine them for determining the most reliable contour line. In particular, numerous algorithms have been developed over time for this procedure, but none of them is validated yet. Accordingly, in this field, there is no ground truth, and research is still active.

Results:

In this work, we developed the Two-Dimensional Segmentation Fusion Tool (TDSFT), a user-friendly tool distributed as a free-to-use standalone application for MAC, Linux, and Windows, which offers a simple and extensible interface where numerous algorithms are proposed to "compute the mean" (i.e., the process to fuse, combine, and "average") multiple 2D lines.

Conclusions:

The TDSFT can support medical specialists, but it can also be used in other fields where it is required to combine 2D close lines. In addition, the TDSFT is designed to be easily extended with new algorithms thanks to a dedicated graphical interface for configuring new parameters. The TDSFT can be downloaded from the following link https//sourceforge.net/p/tdsft.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Bioeng Biotechnol Año: 2024 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Bioeng Biotechnol Año: 2024 Tipo del documento: Article País de afiliación: Italia Pais de publicación: Suiza