A TransUNet model with an adaptive fuzzy focal loss for medical image segmentation

Segmentation of medical images is a critical step in assisting doctors in making accurate diagnoses and planning appropriate treatments. Deep learning architectures often serve as the basis for computer models used for this task. However, a common challenge faced by segmentation models is class imba...

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Veröffentlicht in:	Soft computing (Berlin, Germany) Germany), 2024-10, Vol.28 (20), p.12359-12375
Hauptverfasser:	Talamantes-Roman, Adrian, Ramirez-Alonso, Graciela, Gaxiola, Fernando, Prieto-Ordaz, Olanda, Lopez-Flores, David R.
Format:	Artikel
Sprache:	eng
Schlagworte:	Application of Soft Computing Artificial Intelligence Computational Intelligence Control Encoders-Decoders Engineering Image segmentation Mathematical Logic and Foundations Mechatronics Medical imaging Neural networks Robotics Semantics Statistical analysis
Online-Zugang:	Volltext
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