Abstract. In this study, we present a novel approach utilizing Convolutional Neural Networks (CNNs) based on machine learning for the precise categorization and diagnosis of Soft Tissue Tumors (STTs), specifically focusing on skin tumors. The heterogeneity of STTs poses challenges in accurate disease identification, which our method aims to address. By incorporating innovative data preprocessing techniques for feature extraction and classification, our goal is to improve the automated diagnostic process and reduce misdiagnosis. We explore the application of this approach using multi-parametric magnetic resonance imaging data obtained from patients with skin tumors, with a particular emphasis on accurately delineating tumors for effective radiation therapy planning.
Keywords: Soft Tissues Tumors, Diagnosis and Classification, Soft Tissue Tumor Management, and Machine Learning
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DOI:
10.17148/IJARCCE.2025.14488
