[HTML][HTML] Multi-modal tumor segmentation methods based on deep learning: a narrative review
Methods In in the PubMed and Google Scholar databases, the keywords “multi-
modal”,“deep learning”, and “tumor segmentation” were used to systematically search …
modal”,“deep learning”, and “tumor segmentation” were used to systematically search …
Automatic Delineation and Prognostic Assessment of Head and Neck Tumor Lesion in Multi-Modality Positron Emission Tomography/Computed Tomography Images …
Accurately segmenting and staging tumor lesions in cancer patients presents a significant
challenge for radiologists, but it is essential for devising effective treatment plans including …
challenge for radiologists, but it is essential for devising effective treatment plans including …
Segmentation-free outcome prediction from head and neck cancer PET/CT images: Deep learning-based feature extraction from Multi-Angle Maximum Intensity …
Simple Summary Head and neck cancer is a serious health concern that affects millions of
people across the globe. Predicting how patients will respond to therapy is critical for …
people across the globe. Predicting how patients will respond to therapy is critical for …
[HTML][HTML] MultiTrans: Multi-scale feature fusion transformer with transfer learning strategy for multiple organs segmentation of head and neck CT images
Y He, F Song, W Wu, S Tian, T Zhang, S Zhang… - Medicine in Novel …, 2023 - Elsevier
Radiotherapy with precise segmentation of head and neck organs at risk (OARs) is one of
the important treatment methods for head and neck cancer. In routine clinical practice, OARs …
the important treatment methods for head and neck cancer. In routine clinical practice, OARs …
Scanner agnostic large-scale evaluation of MS lesion delineation tool for clinical MRI
Introduction Patients with MS are MRI scanned continuously throughout their disease course
resulting in a large manual workload for radiologists which includes lesion detection and …
resulting in a large manual workload for radiologists which includes lesion detection and …
UMambaAdj: Advancing GTV Segmentation for Head and Neck Cancer in MRI-Guided RT with UMamba and nnU-Net ResEnc Planner
Magnetic Resonance Imaging (MRI) plays a crucial role in MRI-guided adaptive
radiotherapy for head and neck cancer (HNC) due to its superior soft-tissue contrast …
radiotherapy for head and neck cancer (HNC) due to its superior soft-tissue contrast …
Head and Neck Cancer Segmentation in FDG PET Images: Performance Comparison of Convolutional Neural Networks and Vision Transformers
Convolutional neural networks (CNNs) have a proven track record in medical image
segmentation. Recently, Vision Transformers were introduced and are gaining popularity for …
segmentation. Recently, Vision Transformers were introduced and are gaining popularity for …
Multi-task reconstruction network for synthetic diffusion kurtosis imaging: Predicting neoadjuvant chemoradiotherapy response in locally advanced rectal cancer
Q Ma, Z Liu, J Zhang, C Fu, R Li, Y Sun, T Tong… - European Journal of …, 2024 - Elsevier
Purpose To assess the feasibility and clinical value of synthetic diffusion kurtosis imaging
(DKI) generated from diffusion weighted imaging (DWI) through multi-task reconstruction …
(DKI) generated from diffusion weighted imaging (DWI) through multi-task reconstruction …
LM-UNet: Whole-Body PET-CT Lesion Segmentation with Dual-Modality-Based Annotations Driven by Latent Mamba U-Net
A Liu, D Jia, K Sun, R Meng, M Zhao, Y Jiang… - … Conference on Medical …, 2024 - Springer
PET-CT integrates metabolic information with anatomical structures and plays a vital role in
revealing systemic metabolic abnormalities. Automatic segmentation of lesions from whole …
revealing systemic metabolic abnormalities. Automatic segmentation of lesions from whole …
Advances in Deep Learning for Medical Image Analysis: A Comprehensive Investigation
Medical image analysis is essential for precise diagnosis, optimal treatment planning, non-
invasive monitoring, anomaly detection, advancing medical research, improving patient …
invasive monitoring, anomaly detection, advancing medical research, improving patient …