Self-configuring nnU-Net for automatic delineation of the organs at risk and target in high-dose rate cervical brachytherapy, a low/middle-income country's experience.
Sign Up to like & getrecommendations! Published in 2023 at "Journal of applied clinical medical physics"
DOI: 10.1002/acm2.13988
Abstract: BACKGROUND The high-dose rate (HDR) brachytherapy treatment planning workflow for cervical cancer is a labor-intensive, time-consuming, and expertise-driven process. These issues are amplified in low/middle-income countries with large deficits in experienced healthcare professionals. Automation has… read more here.
Keywords: brachytherapy; dose rate; nnu net; rate ... See more keywords
Automated neonatal nnU-Net brain MRI extractor trained on a large multi-institutional dataset
Sign Up to like & getrecommendations! Published in 2024 at "Scientific Reports"
DOI: 10.1038/s41598-024-54436-8
Abstract: Brain extraction, or skull-stripping, is an essential data preprocessing step for machine learning approaches to brain MRI analysis. Currently, there are limited extraction algorithms for the neonatal brain. We aim to adapt an established deep… read more here.
Keywords: brain mri; brain; nnu net; large multi ... See more keywords
Automatic Segmentation and Detection of Ectopic Eruption of the First Permanent Molars on Panoramic Radiographs Based on nnU-Net.
Sign Up to like & getrecommendations! Published in 2022 at "International journal of paediatric dentistry"
DOI: 10.1111/ipd.12964
Abstract: OBJECTIVES The purpose of this research was to present an artificial intelligence (AI) model which can automatically segment and detect ectopic eruption of the permanent first molars (EMMs) in early mixed dentition on panoramic radiographs… read more here.
Keywords: based nnu; nnu net; model; panoramic radiographs ... See more keywords
Automated 3D segmentation of the hyoid bone in CBCT using nnU-Net v2: a retrospective study on model performance and potential clinical utility
Sign Up to like & getrecommendations! Published in 2025 at "BMC Medical Imaging"
DOI: 10.1186/s12880-025-01797-9
Abstract: This study aimed to identify the hyoid bone (HB) using the nnU-Net based artificial intelligence (AI) model in cone beam computed tomography (CBCT) images and assess the model’s success in automatic segmentation. CBCT images of… read more here.
Keywords: cbct; nnu net; segmentation; performance ... See more keywords
Automated deep learning method for whole-breast segmentation in contrast-free quantitative MRI
Sign Up to like & getrecommendations! Published in 2025 at "BMC Medical Imaging"
DOI: 10.1186/s12880-025-01928-2
Abstract: To develop a deep learning segmentation method utilizing the nnU-Net architecture for fully automated whole-breast segmentation based on diffusion-weighted imaging (DWI) and synthetic MRI (SyMRI) images. A total of 98 patients with 196 breasts were… read more here.
Keywords: deep learning; breast; segmentation; nnu net ... See more keywords
A Fusion Biopsy Framework for Prostate Cancer Based on Deformable Superellipses and nnU-Net
Sign Up to like & getrecommendations! Published in 2022 at "Bioengineering"
DOI: 10.3390/bioengineering9080343
Abstract: In prostate cancer, fusion biopsy, which couples magnetic resonance imaging (MRI) with transrectal ultrasound (TRUS), poses the basis for targeted biopsy by allowing the comparison of information coming from both imaging modalities at the same… read more here.
Keywords: fusion; prostate cancer; prostate; nnu net ... See more keywords
Deep Learning for Caries Detection and Classification
Sign Up to like & getrecommendations! Published in 2021 at "Diagnostics"
DOI: 10.3390/diagnostics11091672
Abstract: Objectives: Deep learning methods have achieved impressive diagnostic performance in the field of radiology. The current study aimed to use deep learning methods to detect caries lesions, classify different radiographic extensions on panoramic films, and… read more here.
Keywords: nnu net; classification; deep learning; caries lesions ... See more keywords
Training and Comparison of nnU-Net and DeepMedic Methods for Autosegmentation of Pediatric Brain Tumors
Sign Up to like & getrecommendations! Published in 2024 at "American Journal of Neuroradiology"
DOI: 10.48550/arxiv.2401.08404
Abstract: BACKGROUND AND PURPOSE: Tumor segmentation is essential in surgical and treatment planning and response assessment and monitoring in pediatric brain tumors, the leading cause of cancer-related death among children. However, manual segmentation is time-consuming and… read more here.
Keywords: pediatric brain; nnu net; segmentation; tumor ... See more keywords