Radiomic analysis of PET images is a promising approach to extract subtler information and
continuously evolves with advances in artificial intelligence. Using deep-learning methods …

Purpose The purpose of this guideline is to provide comprehensive information on best
practices for robust radiomics analyses for both hand-crafted and deep learning-based …

Radiomics describes the extraction of multiple features from medical images, including
molecular imaging modalities, that with bioinformatic approaches, provide additional …

Purpose This study aimed to develop and validate CT-based models to predict pathological
complete response (pCR) after neoadjuvant chemotherapy (NAC) for advanced …

With personalized tumor therapy, understanding and addressing the heterogeneity of
malignant tumors is becoming increasingly important. Heterogeneity can be found within …

Objective This study aimed to determine whether texture parameters could be used in
differentiation between the tumor and the peritumoral tissues based on hybrid 18 F …

Endometrial cancer is the most common gynecologic malignancy in industrialized countries.
Most patients are cured by surgery; however, about 15% of the patients develop recurrence …

Objectives: To analyze the rates, patterns, and features of bone metastases (BM) detected
using 18F-FDG PET/CT in patients with colorectal cancer (CRC) and compare them with …