Results 21 to 30 of about 73,359 (292)
Radiomics for liver tumours [PDF]
Strahlentherapie und Onkologie, 2020 AbstractCurrent research, especially in oncology, increasingly focuses on the integration of quantitative, multiparametric and functional imaging data. In this fast-growing field of research, radiomics may allow for a more sophisticated analysis of imaging data, far beyond the qualitative evaluation of visible tissue changes.
Constantin Dreher +3 more
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Scientific Reports, 2021 Glioblastoma is the most common primary brain tumor. Standard therapy consists of maximum safe resection combined with adjuvant radiochemotherapy followed by chemotherapy with temozolomide, however prognosis is extremely poor.
Alonso Garcia-Ruiz +9 more
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Frontiers in Oncology, 2021 BackgroundWith the improvement of ultrasound imaging resolution and the application of various new technologies, the detection rate of thyroid nodules has increased greatly in recent years. However, there are still challenges in accurately diagnosing the
Shi Yan Guo +4 more
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Radiomics in Nasopharyngeal Carcinoma [PDF]
Clinical Medicine Insights: Oncology, 2022 Nasopharyngeal carcinoma (NPC) is one of the most common head and neck malignancies, and the primary treatment methods are radiotherapy and chemotherapy. Radiotherapy alone, concurrent chemoradiotherapy, and induction chemotherapy combined with concurrent chemoradiotherapy can be used according to different grades. Treatment options and prognoses vary
Wenyue Duan +5 more
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Diagnostics, 2023 In recent years, radiomics has been among the most impactful topics in the research field of quantitative imaging [...]
Zerunian, Marta +2 more
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Deep segmentation networks predict survival of non-small cell lung cancer [PDF]
, 2019 Non-small-cell lung cancer (NSCLC) represents approximately 80-85% of lung cancer diagnoses and is the leading cause of cancer-related death worldwide. Recent studies indicate that image-based radiomics features from positron emission tomography-computed
Allen, Bryan +16 more
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A Rapid Segmentation-Insensitive "Digital Biopsy" Method for Radiomic Feature Extraction: Method and Pilot Study Using CT Images of Non-Small Cell Lung Cancer. [PDF]
, 2016 Quantitative imaging approaches compute features within images' regions of interest. Segmentation is rarely completely automatic, requiring time-consuming editing by experts.
Echegaray, Sebastian +6 more
core +1 more source
Radiomics of Lung Nodules: A Multi-Institutional Study of Robustness and Agreement of Quantitative Imaging Features. [PDF]
, 2016 Radiomics is to provide quantitative descriptors of normal and abnormal tissues during classification and prediction tasks in radiology and oncology. Quantitative Imaging Network members are developing radiomic "feature" sets to characterize tumors, in ...
Balagurunathan, Yoganand +19 more
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Quality of Radiomic Features in Glioblastoma Multiforme: Impact of Semi-Automated Tumor Segmentation Software. [PDF]
, 2017 ObjectiveThe purpose of this study was to evaluate the reliability and quality of radiomic features in glioblastoma multiforme (GBM) derived from tumor volumes obtained with semi-automated tumor segmentation software.Materials and methodsMR images of 45 ...
Jamshidi, Neema +4 more
core +1 more source
Deep learning based identification of bone scintigraphies containing metastatic bone disease foci
Cancer Imaging, 2023 Purpose Metastatic bone disease (MBD) is the most common form of metastases, most frequently deriving from prostate cancer. MBD is screened with bone scintigraphy (BS), which have high sensitivity but low specificity for the diagnosis of MBD, often ...
Abdalla Ibrahim +18 more
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