AIMC Topic: Sarcoma

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Differentiation of canine and feline neoplasms using multi-modal imaging and machine learning.

Scientific reports
Canine/feline (sub-)cutaneous tumors, which include lipomas, mastocytomas and soft tissue sarcomas, introduce diagnostic challenges due to inherent tissue heterogeneity, accompanied by diverse clinical pathogenesis. Current study integrates conventio...

Prediction of prognosis using artificial intelligence-based histopathological image analysis in patients with soft tissue sarcomas.

Cancer medicine
BACKGROUND: Prompt histopathological diagnosis with accuracy is required for soft tissue sarcomas (STSs) which are still challenging. In addition, the advances in artificial intelligence (AI) along with the development of pathology slides digitizatio...

MRI-Based Deep Learning Segmentation and Radiomics of Sarcoma in Mice.

Tomography (Ann Arbor, Mich.)
Small-animal imaging is an essential tool that provides noninvasive, longitudinal insight into novel cancer therapies. However, considerable variability in image analysis techniques can lead to inconsistent results. We have developed quantitative ima...

Deep multi-modality collaborative learning for distant metastases predication in PET-CT soft-tissue sarcoma studies.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Soft-tissue Sarcomas (STS) are a heterogeneous group of malignant neoplasms with a relatively high mortality rate from distant metastases. Early prediction or quantitative evaluation of distant metastases risk for patients with STS is an important st...