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9 ta ish

Ish: Choise of Statistical Processing Methods for the Results of Radcomic Analysis of CT Images of Head and Neck Tumors

  1. LIFEx: A Freeware for Radiomic Feature Calculation in Multimodality Imaging to Accelerate Advances in the Characterization of Tumor Heterogeneity

    Christophe Nioche, Fanny Orlhac, Sarah Boughdad +7

    Maqola20183 iqtibos
    ABI

  2. Texture Analysis Methods for Medical Image Characterisation

    W. Brien Henry

    Bob20102 iqtibos
    ABI

  3. CT perfusion in oncology: how to do it

    Giuseppe Petralia, Luke Bonello, Stefano Viotti +3

    Sharh maqola20102 iqtibos
    ABI

  4. Intratumor heterogeneity: Nature and biological significance

    Tatiana S. Gerashchenko, Evgeny V. Denisov, Н. В. Литвяков +5

    Sharh maqola20132 iqtibos
    ABI

  5. Computed Tomography Radiomics Predicts HPV Status and Local Tumor Control After Definitive Radiochemotherapy in Head and Neck Squamous Cell Carcinoma

    Marta Bogowicz, Oliver Riesterer, Kristian Ikenberg +5

    Maqola20172 iqtibos
    ABI

  6. Cancer Metabolism and Tumor Heterogeneity: Imaging Perspectives Using MR Imaging and Spectroscopy

    Gigin Lin, Kayvan R. Keshari, Jae Mo Park

    Sharh maqola20172 iqtibos
    ABI

  7. Prediction of Tumor Grade and Nodal Status in Oropharyngeal and Oral Cavity Squamous-cell Carcinoma Using a Radiomic Approach

    Valeria Romeo, Renato Cuocolo, Carlo Ricciardi +10

    Maqola20192 iqtibos
    ABI

  8. Machine Learning–Based MRI Texture Analysis to Predict the Histologic Grade of Oral Squamous Cell Carcinoma

    Jiliang Ren, Meng Qi, Ying Yuan +2

    Maqola20202 iqtibos
    ABI

  9. Sarlavhasiz

    Boshqa1 iqtibos
    ABI