Clinically Applicable Segmentation of Head and Neck Anatomy for Radiotherapy: Deep Learning Algorithm Development and Validation Study

• Main Authors: Stanislav Nikolov (Author), Sam Blackwell (Author), Alexei Zverovitch (Author), Ruheena Mendes (Author), Michelle Livne (Author), Jeffrey De Fauw (Author), Yojan Patel (Author), Clemens Meyer (Author), Harry Askham (Author), Bernadino Romera-Paredes (Author), Christopher Kelly (Author), Alan Karthikesalingam (Author), Carlton Chu (Author), Dawn Carnell (Author), Cheng Boon (Author), Derek D'Souza (Author), Syed Ali Moinuddin (Author), Bethany Garie (Author), Yasmin McQuinlan (Author), Sarah Ireland (Author), Kiarna Hampton (Author), Krystle Fuller (Author), Hugh Montgomery (Author), Geraint Rees (Author), Mustafa Suleyman (Author), Trevor Back (Author), Cían Owen Hughes (Author), Joseph R Ledsam (Author), Olaf Ronneberger (Author)
• Format: Book
• Published: JMIR Publications, 2021-07-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

BackgroundOver half a million individuals are diagnosed with head and neck cancer each year globally. Radiotherapy is an important curative treatment for this disease, but it requires manual time to delineate radiosensitive organs at risk. This planning process can delay treatment while also introdu...