ArticleInternational journal of computer assisted radiology and surgery2024
PitSurgRT: real-time localization of critical anatomical structures in endoscopic pituitary surgery.
Article in International journal of computer assisted radiology and surgery, 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, 16 citations in OpenAlex.
- First-in-human evaluation of real-time pixel-level AI-assisted anatomical segmentation in neurosurgery: pituitary surgery as an exemplar.Pituitary · 2026Article
- Artificial intelligence in pituitary surgery: the path to clinical solutions.Endocrine-related cancer · 2026Review
- Deep Learning for Automatic Segmentation of Pituitary Adenomas: A Videomics Study.Operative neurosurgery (Hagerstown, Md.) · 2026Article
- Morphological and Epidemiological Analysis of the Sphenoid Sinus Based on Computed Tomography and Magnetic Resonance Imaging: A Narrative Review.Life (Basel, Switzerland) · 2026Review
- The Role of Virtual and Augmented Reality in Transsphenoidal Surgical Approaches to the Sellar and Parasellar Area-A Systematic Review.Journal of clinical medicine · 2026Review
- A High-Quality Endoscopic Image Dataset with Annotated Recurrent Laryngeal Nerve for AI-Assisted Thyroid Surgery.Scientific data · 2026Article
- Article
- ConsisTNet: a spatio-temporal approach for consistent anatomical localization in endoscopic pituitary surgery.International journal of computer assisted radiology and surgery · 2025Article
- Artificial intelligence-driven approaches in pituitary neuroendocrine tumors: integrating endocrine-metabolic profiling for enhanced diagnostics and therapeutics.Frontiers in endocrinology · 2025Review
- PitRSDNet: Predicting intra-operative remaining surgery duration in endoscopic pituitary surgery.Healthcare technology letters · 2024Article
- Artificial intelligence assisted operative anatomy recognition in endoscopic pituitary surgery.NPJ digital medicine · 2024Article
- Laparoscopic image segmentation of the hepatobiliary system: Current status and advances from a deep learning perspective.Digital healthReview
Corrections and comments
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
Abstract
purposeEndoscopic pituitary surgery entails navigating through the nasal cavity and sphenoid sinus to access the sella using an endoscope. This procedure is intricate due to the proximity of crucial anatomical structures (e.g. carotid arteries and optic nerves) to pituitary tumours, and any unintended damage can lead to severe complications including blindness and death. Intraoperative guidance during this surgery could support improved localization of the critical structures leading to reducing the risk of complications.
methodsA deep learning network PitSurgRT is proposed for real-time localization of critical structures in endoscopic pituitary surgery. The network uses high-resolution net (HRNet) as a backbone with a multi-head for jointly localizing critical anatomical structures while segmenting larger structures simultaneously. Moreover, the trained model is optimized and accelerated by using TensorRT. Finally, the model predictions are shown to neurosurgeons, to test their guidance capabilities.
resultsCompared with the state-of-the-art method, our model significantly reduces the mean error in landmark detection of the critical structures from 138.76 to 54.40 pixels in a 1280
conclusionThe results from the quantitative evaluation, real-time acceleration, and neurosurgeon study demonstrate the proposed method is highly promising in providing real-time intraoperative guidance of the critical anatomical structures in endoscopic pituitary surgery.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.