Jinguji M - Search Results

1

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

Nakajo M, Hirahara D, Jinguji M, Hirahara M, Tani A, Nagano H, Takumi K, Kamimura K, Kanzaki F, Yamashita M, Yoshiura T. Nakajo M, et al. Among authors: jinguji m. Jpn J Radiol. 2024 Sep 10. doi: 10.1007/s11604-024-01649-6. Online ahead of print. Jpn J Radiol. 2024. PMID: 39254903

2

The value of intratumoral heterogeneity of (18)F-FDG uptake to differentiate between primary benign and malignant musculoskeletal tumours on PET/CT.

Nakajo M, Nakajo M, Jinguji M, Fukukura Y, Nakabeppu Y, Tani A, Yoshiura T. Nakajo M, et al. Among authors: jinguji m. Br J Radiol. 2015;88(1055):20150552. doi: 10.1259/bjr.20150552. Epub 2015 Sep 4. Br J Radiol. 2015. PMID: 26337605 Free PMC article.

3

The clinical value of texture analysis of dual-time-point ¹⁸F-FDG-PET/CT imaging to differentiate between ¹⁸F-FDG-avid benign and malignant pulmonary lesions.

Nakajo M, Jinguji M, Aoki M, Tani A, Sato M, Yoshiura T. Nakajo M, et al. Among authors: jinguji m. Eur Radiol. 2020 Mar;30(3):1759-1769. doi: 10.1007/s00330-019-06463-7. Epub 2019 Nov 14. Eur Radiol. 2020. PMID: 31728684

4

Application of a machine learning approach to characterization of liver function using ^99mTc-GSA SPECT/CT.

Nakajo M, Jinguji M, Tani A, Hirahara D, Nagano H, Takumi K, Yoshiura T. Nakajo M, et al. Among authors: jinguji m. Abdom Radiol (NY). 2021 Jul;46(7):3184-3192. doi: 10.1007/s00261-021-02985-1. Epub 2021 Mar 6. Abdom Radiol (NY). 2021. PMID: 33675380

5

Application of a Machine Learning Approach for the Analysis of Clinical and Radiomic Features of Pretreatment [¹⁸F]-FDG PET/CT to Predict Prognosis of Patients with Endometrial Cancer.

Nakajo M, Jinguji M, Tani A, Kikuno H, Hirahara D, Togami S, Kobayashi H, Yoshiura T. Nakajo M, et al. Among authors: jinguji m. Mol Imaging Biol. 2021 Oct;23(5):756-765. doi: 10.1007/s11307-021-01599-9. Epub 2021 Mar 24. Mol Imaging Biol. 2021. PMID: 33763816

6

Machine learning based evaluation of clinical and pretreatment ¹⁸F-FDG-PET/CT radiomic features to predict prognosis of cervical cancer patients.

Nakajo M, Jinguji M, Tani A, Yano E, Hoo CK, Hirahara D, Togami S, Kobayashi H, Yoshiura T. Nakajo M, et al. Among authors: jinguji m. Abdom Radiol (NY). 2022 Feb;47(2):838-847. doi: 10.1007/s00261-021-03350-y. Epub 2021 Nov 25. Abdom Radiol (NY). 2022. PMID: 34821963

7

The efficacy of ¹⁸F-FDG-PET-based radiomic and deep-learning features using a machine-learning approach to predict the pathological risk subtypes of thymic epithelial tumors.

Nakajo M, Takeda A, Katsuki A, Jinguji M, Ohmura K, Tani A, Sato M, Yoshiura T. Nakajo M, et al. Among authors: jinguji m. Br J Radiol. 2022 Jun 1;95(1134):20211050. doi: 10.1259/bjr.20211050. Epub 2022 Mar 28. Br J Radiol. 2022. PMID: 35312337 Free PMC article.

8

The Usefulness of Machine Learning-Based Evaluation of Clinical and Pretreatment [¹⁸F]-FDG-PET/CT Radiomic Features for Predicting Prognosis in Hypopharyngeal Cancer.

Nakajo M, Kawaji K, Nagano H, Jinguji M, Mukai A, Kawabata H, Tani A, Hirahara D, Yamashita M, Yoshiura T. Nakajo M, et al. Among authors: jinguji m. Mol Imaging Biol. 2023 Apr;25(2):303-313. doi: 10.1007/s11307-022-01757-7. Epub 2022 Jul 21. Mol Imaging Biol. 2023. PMID: 35864282

9

Application of ¹²³I-MIBG myocardial maximum standardized uptake value to characterize cardiac function in patients with pheochromocytoma: comparison with echocardiography.

Nakajo M, Horizoe Y, Kawaji K, Jinguji M, Tani A, Fukukura Y, Ohishi M, Yoshiura T. Nakajo M, et al. Among authors: jinguji m. Jpn J Radiol. 2023 Apr;41(4):437-448. doi: 10.1007/s11604-022-01365-z. Epub 2022 Nov 28. Jpn J Radiol. 2023. PMID: 36441441 Free PMC article.

10

Application of Machine Learning Analyses Using Clinical and [¹⁸F]-FDG-PET/CT Radiomic Characteristics to Predict Recurrence in Patients with Breast Cancer.

Kawaji K, Nakajo M, Shinden Y, Jinguji M, Tani A, Hirahara D, Kitazono I, Ohtsuka T, Yoshiura T. Kawaji K, et al. Among authors: jinguji m. Mol Imaging Biol. 2023 Oct;25(5):923-934. doi: 10.1007/s11307-023-01823-8. Epub 2023 May 16. Mol Imaging Biol. 2023. PMID: 37193804

Save citations to file

Email citations

Send citations to clipboard

Add to Collections

Add to My Bibliography

Create a file for external citation management software

Your saved search

Your RSS Feed

My Custom Filters

Publication date

Text availability

Article attribute

Article type

Article Language

Species

Sex

Age

Other

63 results

Search Page

Filters