Machine Learning Applications for Head and Neck Imaging

被引:9
|
作者
Maleki, Farhad [1 ,2 ]
Le, William Trung [3 ]
Sananmuang, Thiparom [4 ]
Kadoury, Samuel [3 ,5 ]
Forghani, Reza [1 ,2 ,6 ,7 ,8 ,9 ]
机构
[1] McGill Univ, Augmented Intelligence & Precis Hlth Lab AIPHL, Dept Radiol, Hlth Ctr, 5252 Blvd Maisonneuve Ouest, Montreal, PQ H4A 3S5, Canada
[2] McGill Univ, Res Inst, Hlth Ctr, 5252 Blvd Maisonneuve Ouest, Montreal, PQ H4A 3S5, Canada
[3] Polytech Montreal, POB 6079,Succ Ctr Ville, Montreal, PQ H3C 3A7, Canada
[4] Ramathibodi Hosp, Dept Diagnost & Therapeut Radiol & Res, Fac Med, Bangkok 10400, Thailand
[5] CHUM Res Ctr, 900 St Denis St, Montreal, PQ H2X 0A9, Canada
[6] McGill Univ, Dept Radiol, 1650 Cedar Ave, Montreal, PQ H3G 1A4, Canada
[7] Jewish Gen Hosp, Segal Canc Ctr, Lady Davis Inst Med Res, 3755 Cote Ste Catherine Rd, Montreal, PQ H3T 1E2, Canada
[8] McGill Univ, Gerald Bronfman Dept Oncol, Suite 720,5100 Maisonneuve Blvd West, Montreal, PQ H4A 3T2, Canada
[9] McGill Univ, Royal Victoria Hosp, Dept Otolaryngol Head & Neck Surg, Hlth Ctr, 1001 Boul Decarie Blvd, Montreal, PQ H3A 3J1, Canada
关键词
Head and neck imaging; Autosegmentation; Classification; Machine learning; Deep learning; Convolutional neural network; Artificial intelligence; Head and neck cancer; TOMOGRAPHY PHYSICAL PRINCIPLES; CT TEXTURE ANALYSIS; ARTIFICIAL-INTELLIGENCE; THYROID-CANCER; HPV STATUS; RADIOMICS; PREDICTION; IMAGES; ULTRASOUND; CLASSIFICATION;
D O I
10.1016/j.nic.2020.08.003
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
The head and neck (HN) consists of a large number of vital anatomic structures within a compact area. Imaging plays a central role in the diagnosis and management of major disorders affecting the HN. This article reviews the recent applications of machine learning (ML) in HN imaging with a focus on deep learning approaches. It categorizes ML applications in HN imaging into deep learning and traditional ML applications and provides examples of each category. It also discusses the main challenges facing the successful deployment of ML-based applications in the clinical setting and provides suggestions for addressing these challenges.
引用
收藏
页码:517 / +
页数:15
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