Deep learning-based automatic delineation of anal cancer gross tumour volume: a multimodality comparison of CT, PET and MRI.
Aurora Rosvoll GroendahlYngve Mardal Mardal MoeChristine Kiran KaushalBao Ngoc HuynhEspen RustenOliver TomicEivor HernesBettina HanekampChristine UndsethMarianne Grønlie GurenEirik MalinenCecilia Marie FutsaetherPublished in: Acta oncologica (Stockholm, Sweden) (2021)
CNNs provided high-quality automatic GTV delineations for both single and multimodality image input, indicating that deep learning may prove a versatile tool for target volume delineation in future patients with ASCC.
Keyphrases
- deep learning
- contrast enhanced
- artificial intelligence
- computed tomography
- convolutional neural network
- papillary thyroid
- positron emission tomography
- magnetic resonance imaging
- machine learning
- image quality
- squamous cell
- high grade
- dual energy
- current status
- diffusion weighted imaging
- squamous cell carcinoma
- lymph node metastasis
- pet imaging
- childhood cancer
- clinical evaluation