ArticleInternational journal of computer assisted radiology and surgery2019
Toward an automatic preoperative pipeline for image-guided temporal bone surgery.
Article in International journal of computer assisted radiology and surgery, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Synchrotron-Based Deep Learning Network of the Inner Ear: Development and Expert Validation.The Laryngoscope · 2026Article
- Exploring Artificial Intelligence in Orthopedic Surgery: A Review of Perception, Decision, and Execution Systems.Sensors (Basel, Switzerland) · 2026Review
- Image-based deep learning in otology: a state-of-the-art review.Frontiers in neurology · 2026Review
- Systematic and Individualized Preparation of External Ear Canal Implants: Development and Validation of an Efficient and Accurate Automated Segmentation System.Journal of imaging · 2025Article
- LL-MAROCO: A Large Language Model-Assisted Robotic System for Oral and Craniomaxillofacial Osteotomy.Bioengineering (Basel, Switzerland) · 2025Article
- Artificial Intelligence Assurance in Head and Neck Surgery: Now and Next.Proceedings. IEEE International Symposium on Computer-Based Medical Systems · 2025Article
- Automated Volumetric Milling Area Planning for Acoustic Neuroma Surgery via Evolutionary Multi-Objective Optimization.Sensors (Basel, Switzerland) · 2025Article
- Modern Image-Guided Surgery: A Narrative Review of Medical Image Processing and Visualization.Sensors (Basel, Switzerland) · 2023Review
- Towards fully automated inner ear analysis with deep-learning-based joint segmentation and landmark detection framework.Scientific reports · 2023Article
- A Self-Configuring Deep Learning Network for Segmentation of Temporal Bone Anatomy in Cone-Beam CT Imaging.Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery · 2023Article
- Diagnosis, Treatment, and Management of Otitis Media with Artificial Intelligence.Diagnostics (Basel, Switzerland) · 2023Review
- Research and application progress in deep learning in otology.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2023Article
- A Web-Based Automated Image Processing Research Platform for Cochlear Implantation-Related Studies.Journal of clinical medicine · 2022Article
- Automated Registration-Based Temporal Bone Computed Tomography Segmentation for Applications in Neurotologic Surgery.Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery · 2022Article
- Automated objective surgical planning for lateral skull base tumors.International journal of computer assisted radiology and surgery · 2022Article
- Application value of a deep learning method based on a 3D V-Net convolutional neural network in the recognition and segmentation of the auditory ossicles.Frontiers in neuroinformatics · 2022Article
- Cranio-maxillofacial post-operative face prediction by deep spatial multiband VGG-NET CNN.American journal of translational research · 2022Article
- Fully automated segmentation in temporal bone CT with neural network: a preliminary assessment study.BMC medical imaging · 2021Article
- A Fully Automated Analytic System for Measuring Endolymphatic Hydrops Ratios in Patients With Ménière Disease via Magnetic Resonance Imaging: Deep Learning Model Development Study.Journal of medical Internet research · 2021Article
- Deep learning for the fully automated segmentation of the inner ear on MRI.Scientific reports · 2021Observational
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Authors and funding
8 authors.
Funding
Abstract
purposeMinimally invasive surgery is often built upon a time-consuming preoperative step consisting of segmentation and trajectory planning. At the temporal bone, a complete automation of these two tasks might lead to faster interventions and more reproducible results, benefiting clinical workflow and patient health.
methodsWe propose an automatic segmentation and trajectory planning pipeline for image-guided interventions at the temporal bone. For segmentation, we use a shape regularized deep learning approach that is capable of automatically detecting even the cluttered tiny structures specific for this anatomy. We then perform trajectory planning for both linear and nonlinear interventions on these automatically segmented risk structures.
resultsWe evaluate the usability of segmentation algorithms for planning access canals to the cochlea and the internal auditory canal on 24 CT data sets of real patients. Our new approach achieves similar results to the existing semiautomatic method in terms of Dice but provides more accurate organ shapes for the subsequent trajectory planning step. The source code of the algorithms is publicly available.
conclusionAutomatic segmentation and trajectory planning for various clinical procedures at the temporal bone are feasible. The proposed automatic pipeline leads to an efficient and unbiased workflow for preoperative planning.
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