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Found 5 papers, 2 papers with code
SegRap2023: A Benchmark of Organs-at-Risk and Gross Tumor Volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma
The precise delineation of Gross Tumor Volumes (GTVs) and Organs-At-Risk (OARs) is crucial in radiation treatment, directly impacting patient prognosis.
Fully Automatic Segmentation of Gross Target Volume and Organs-at-Risk for Radiotherapy Planning of Nasopharyngeal Carcinoma
Target segmentation in CT images of Head&Neck (H&N) region is challenging due to low contrast between adjacent soft tissue.
AutoPaint: A Self-Inpainting Method for Unsupervised Anomaly Detection
This work intends to, first, propose a robust inpainting model to learn the details of healthy anatomies and reconstruct high-resolution images by preserving anatomical constraints.
PriorNet: lesion segmentation in PET-CT including prior tumor appearance information
Tumor segmentation in PET-CT images is challenging due to the dual nature of the acquired information: low metabolic information in CT and low spatial resolution in PET.
Development and evaluation of a 3D annotation software for interactive COVID-19 lesion segmentation in chest CT
Segmentation of COVID-19 lesions from chest CT scans is of great importance for better diagnosing the disease and investigating its extent.
