Mitsuho Hirahara

Kagoshima, 8908544, Japan

Last Updated: 09/26/2026

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Found 10 publications

Machine learning models using 18F-FDG PET/CT radiomics for RAS mutation prediction and prognostic stratification in colorectal cancer.

Machine learning models using 18F-FDG PET/CT radiomics for RAS mutation prediction and prognostic stratification in colorectal cancer.

Journal: The British journal of radiology

Published: January 13, 2026

Artificial intelligence in oncological positron emission tomography: advancing image analysis and interpretation.

Artificial intelligence in oncological positron emission tomography: advancing image analysis and interpretation.

Journal: Clinical radiology

Published: May 07, 2025

Use of relative Patlak plot Ki' images as an alternative to standard Patlak plot Ki images in clinical practice.

Use of relative Patlak plot Ki' images as an alternative to standard Patlak plot Ki images in clinical practice.

Journal: EJNMMI research

Published: March 20, 2025

Electron density derived from dual-energy CT for predicting thrombolytic therapeutic efficacy in patients with pulmonary embolism.

Electron density derived from dual-energy CT for predicting thrombolytic therapeutic efficacy in patients with pulmonary embolism.

Journal: Japanese journal of radiology

Published: December 15, 2024

Machine learning-based prognostic modeling in gallbladder cancer using clinical data and pre-treatment [18F]-FDG-PET-radiomic features.

Machine learning-based prognostic modeling in gallbladder cancer using clinical data and pre-treatment [18F]-FDG-PET-radiomic features.

Journal: Japanese journal of radiology

Published: September 26, 2024

Applying deep learning-based ensemble model to [18F]-FDG-PET-radiomic features for differentiating benign from malignant parotid gland diseases.

Applying deep learning-based ensemble model to [18F]-FDG-PET-radiomic features for differentiating benign from malignant parotid gland diseases.

Journal: Japanese journal of radiology

Published: July 19, 2024

Usefulness of the Primary Tumor Standardized Uptake Value of Iodine-123 Metaiodobenzylguanidine for Predicting Metastatic Potential in Pheochromocytoma and Paraganglioma.

Usefulness of the Primary Tumor Standardized Uptake Value of Iodine-123 Metaiodobenzylguanidine for Predicting Metastatic Potential in Pheochromocytoma and Paraganglioma.

Journal: Molecular imaging and biology

Published: June 14, 2024

Machine learning approach using 18F-FDG-PET-radiomic features and the visibility of right ventricle 18F-FDG uptake for predicting clinical events in patients with cardiac sarcoidosis.

Machine learning approach using 18F-FDG-PET-radiomic features and the visibility of right ventricle 18F-FDG uptake for predicting clinical events in patients with cardiac sarcoidosis.

Journal: Japanese journal of radiology

Published: December 20, 2023

Clinical application of 18F-fluorodeoxyglucose positron emission tomography/computed tomography radiomics-based machine learning analyses in the field of oncology.

Clinical application of 18F-fluorodeoxyglucose positron emission tomography/computed tomography radiomics-based machine learning analyses in the field of oncology.

Journal: Japanese journal of radiology

Published: July 10, 2023

CT and MRI features of undifferentiated carcinomas with osteoclast-like giant cells of the pancreas: a case series.

CT and MRI features of undifferentiated carcinomas with osteoclast-like giant cells of the pancreas: a case series.

Journal: Abdominal radiology (New York)

Published: March 01, 2019

Showing 1-10 of 10

Last Updated: 09/26/2026