Multiparametric MRI-based habitat analysis integrating deep learning and radiomics for predicting preoperative Ki-67 expression level in breast cancer

Abstract Background Breast cancer (BC) is the most common malignant tumor in women globally. Ki-67, a vital marker for prognosis, is currently detected invasively. Non-invasive magnetic resonance imaging (MRI) prediction faces challenges due to intratumoral heterogeneity. Materials and methods This...

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Päätekijät:	Yuqian Wang, Yue Zhang, Zaiyi Liu, Yiming Xiong, Mifang Li, Lingyan Zhang, Zhenwei Shi
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	BMC 2026-01-01
Sarja:	BMC Medical Imaging
Aiheet:	Breast cancer Radiomics Habitat Machine learning Deep learning Ki-67 expression level
Linkit:	https://doi.org/10.1186/s12880-026-02151-3
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