Artificial intelligence and machine learning for medical imaging: A technology review

A Barragán-Montero, U Javaid, G Valdés, D Nguyen… - Physica Medica, 2021 - Elsevier
Artificial intelligence (AI) has recently become a very popular buzzword, as a consequence
of disruptive technical advances and impressive experimental results, notably in the field of …

A review of deep learning based methods for medical image multi-organ segmentation

Y Fu, Y Lei, T Wang, WJ Curran, T Liu, X Yang - Physica Medica, 2021 - Elsevier
Deep learning has revolutionized image processing and achieved the-state-of-art
performance in many medical image segmentation tasks. Many deep learning-based …

[HTML][HTML] Clinically applicable segmentation of head and neck anatomy for radiotherapy: deep learning algorithm development and validation study

S Nikolov, S Blackwell, A Zverovitch, R Mendes… - Journal of medical …, 2021 - jmir.org
Background: Over 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 …

Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy

S Nikolov, S Blackwell, A Zverovitch, R Mendes… - arxiv preprint arxiv …, 2018 - arxiv.org
Over half a million individuals are diagnosed with head and neck cancer each year
worldwide. Radiotherapy is an important curative treatment for this disease, but it requires …

Auto‐segmentation of organs at risk for head and neck radiotherapy planning: from atlas‐based to deep learning methods

T Vrtovec, D Močnik, P Strojan, F Pernuš… - Medical …, 2020 - Wiley Online Library
Radiotherapy (RT) is one of the basic treatment modalities for cancer of the head and neck
(H&N), which requires a precise spatial description of the target volumes and organs at risk …

Automatic segmentation of mandible from conventional methods to deep learning—a review

B Qiu, H van der Wel, J Kraeima, HH Glas… - Journal of personalized …, 2021 - mdpi.com
Medical imaging techniques, such as (cone beam) computed tomography and magnetic
resonance imaging, have proven to be a valuable component for oral and maxillofacial …

A preliminary experience of implementing deep-learning based auto-segmentation in head and neck cancer: a study on real-world clinical cases

Y Zhong, Y Yang, Y Fang, J Wang, W Hu - Frontiers in oncology, 2021 - frontiersin.org
Purpose While artificial intelligence has shown great promise in organs-at-risk (OARs) auto
segmentation for head and neck cancer (HNC) radiotherapy, to reach the level of clinical …

Is attention all you need in medical image analysis? A review.

G Papanastasiou, N Dikaios, J Huang… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Medical imaging is a key component in clinical diagnosis, treatment planning and clinical
trial design, accounting for almost 90% of all healthcare data. CNNs achieved performance …

Automatic detection and segmentation of multiple brain metastases on magnetic resonance image using asymmetric UNet architecture

Y Cao, A Vassantachart, CY Jason, C Yu… - Physics in Medicine …, 2021 - iopscience.iop.org
Detection of brain metastases is a paramount task in cancer management due both to the
number of high-risk patients and the difficulty of achieving consistent detection. In this study …

Deep learning algorithm performance in contouring head and neck organs at risk: a systematic review and single-arm meta-analysis

P Liu, Y Sun, X Zhao, Y Yan - BioMedical Engineering OnLine, 2023 - Springer
Purpose The contouring of organs at risk (OARs) in head and neck cancer radiation
treatment planning is a crucial, yet repetitive and time-consuming process. Recent studies …