Implementing a deep learning model for automatic tongue tumour segmentation in ex-vivo 3-dimensional ultrasound volumes

Author:

Bekedam N.M.,Idzerda L.H.W.,van Alphen M.J.A.,van Veen R.L.P.,Karssemakers L.H.E.,Karakullukcu M.B.,Smeele L.E.

Publisher

Elsevier BV

Reference22 articles.

1. Hunter K, Da Forno P, Hall G, et al. Standards and datasets for reporting cancers. Dataset for the histopathological reporting of carcinomas of the oral cavity. The Royal College of Pathologists, 2023. Available from URL: https://www.rcpath.org/static/c4a9faf7-393a-4ba8-9532f719d8cdff3b/7b0a5709-ce18-4694-8e4c84a4ffd466f2/Dataset-for-histopathology-reporting-of-carcinomas-of-the-oral-cavity.pdf (last accessed 12 February 2024).

2. Resection margins in oral cancer surgery: room for improvement;Smits;Head Neck,2016

3. Intraoral ultrasonography to measure tumor thickness of oral cancer: a systematic review and meta-analysis;Klein Nulent;Oral Oncol,2018

4. The oral cavity tumor thickness: measurement accuracy and consequences for tumor staging;Brouwer de Koning;Eur J Surg Oncol,2019

5. Preoperative evaluation of depth of invasion in oral tongue squamous cell carcinoma: a systematic review and meta-analysis;Voizard;Oral Oncol,2023

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