ArticleBMC medical imaging2024
nnU-Net based segmentation and 3D reconstruction of uterine fibroids with MRI images for HIFU surgery planning.
Article in BMC medical imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Reconstruction from multi-planar MRI with foundation models for uterine fibroid analysis.NPJ digital medicine · 2026Article
- Segmentation and diagnosis of anterior cruciate ligament tear using deep learning and radiomics based on knee CT.BMC medical imaging · 2026Article
- Multi-centric AI Model for Unruptured Intracranial Aneurysm Detection and Volumetric Segmentation in 3D TOF-MRI.Journal of imaging informatics in medicine · 2026Article
- Precision surgery in the era of 3D visualization, AR/VR, and 3D printing: current applications and future directions.Frontiers in medicine · 2026Review
- Uterine cancer classification from CT images using convolutional feature extraction and transformer-based self-attention.Frontiers in medicine · 2026Article
- Application of 3D reconstruction combined with 3D printing and CBL + SP in teaching gynecologic malignant tumors.Frontiers in medicine · 2026Article
- Efficiency of Artificial Intelligence in Three-Dimensional Reconstruction of Medical Imaging.Cureus · 2025Review
- Artificial Intelligence and Uterine Fibroids: A Useful Combination for Diagnosis and Treatment.Journal of clinical medicine · 2025Review
- MAF-net: multi-receptive attention fusion network with dual-path squeeze-and-excitation enhancement module for uterine fibroid segmentation.Frontiers in physiology · 2025Article
- Three-dimensional visualization and navigation for micro-noninvasive uterine fibroid surgery based on MRI and ultrasound image fusion.Frontiers in artificial intelligence · 2025Article
- Artificial intelligence-assisted radiation imaging pathways for distinguishing uterine fibroids and malignant lesions in patients presenting with cancer pain: a literature review.Frontiers in oncology · 2025Review
- 3D segmentation of uterine fibroids based on deep supervision and an attention gate.Frontiers in oncology · 2025Article
Corrections and comments
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
High-Intensity Focused Ultrasound (HIFU) ablation represents a rapidly advancing non-invasive treatment modality that has achieved considerable success in addressing uterine fibroids, which constitute over 50% of benign gynecological tumors. Preoperative Magnetic Resonance Imaging (MRI) plays a pivotal role in the planning and guidance of HIFU surgery for uterine fibroids, wherein the segmentation of tumors holds critical significance. The segmentation process was previously manually executed by medical experts, entailing a time-consuming and labor-intensive procedure heavily reliant on clinical expertise. This study introduced deep learning-based nnU-Net models, offering a cost-effective approach for their application in the segmentation of uterine fibroids utilizing preoperative MRI images. Furthermore, 3D reconstruction of the segmented targets was implemented to guide HIFU surgery. The evaluation of segmentation and 3D reconstruction performance was conducted with a focus on enhancing the safety and effectiveness of HIFU surgery. Results demonstrated the nnU-Net's commendable performance in the segmentation of uterine fibroids and their surrounding organs. Specifically, 3D nnU-Net achieved Dice Similarity Coefficients (DSC) of 92.55% for the uterus, 95.63% for fibroids, 92.69% for the spine, 89.63% for the endometrium, 97.75% for the bladder, and 90.45% for the urethral orifice. Compared to other state-of-the-art methods such as HIFUNet, U-Net, R2U-Net, ConvUNeXt and 2D nnU-Net, 3D nnU-Net demonstrated significantly higher DSC values, highlighting its superior accuracy and robustness. In conclusion, the efficacy of the 3D nnU-Net model for automated segmentation of the uterus and its surrounding organs was robustly validated. When integrated with intra-operative ultrasound imaging, this segmentation method and 3D reconstruction hold substantial potential to enhance the safety and efficiency of HIFU surgery in the clinical treatment of uterine fibroids.
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