Hiroaki Takahashi

No ORCID on file · 5 papers in corpus · active 2023-2025

Study types

  • article 3
  • preprint 1
  • review 1

Condition tags

  • endometriosis 3
article 2025
Advancing endometriosis detection in daily practice: a deep learning-enhanced multi-sequence MRI analytical model
Abdominal radiology (New York) ·doi:10.1007/s00261-025-04942-8

BACKGROUND AND PURPOSE: Endometriosis affects 5-10% of women of reproductive age. Despite its prevalence, diagnosing endometriosis through imaging remains challenging. Advances in deep learning (DL) are revolutionizing the diagnosis and man…

article 2025
Proposed new MRI scoring system of rectosigmoid endometriosis to guide operative planning
Abdominal radiology (New York) ·doi:10.1007/s00261-025-05021-8

BACKGROUND: Rectosigmoid endometriosis (RSE) presents with a diverse array of MRI findings that impact surgical planning. No standardized reporting and data system has been established for RSE. PURPOSE: We propose a novel MRI scoring syste…

preprint 2025
Proposed New MRI Scoring System of Rectosigmoid Endometriosis to Guide Operative Planning
·doi:10.21203/rs.3.rs-6336241/v1
article 2023
#196 Artificial intelligence-based model for transvaginal ultrasound early detection of endometrial atypical hyperplasia and endometrial cancer in women with postmenopausal bleeding
·doi:10.1136/ijgc-2023-esgo.54
review 2023
Potential applications of PET/MRI in non-oncologic conditions within the abdomen and pelvis
Abdominal radiology (New York) ·doi:10.1007/s00261-023-03922-0

PET/MRI is a relatively new imaging modality with several advantages over PET/CT that promise to improve imaging of the abdomen and pelvis for specific diagnostic tasks by combining the superior soft tissue characterization of MRI with the …