Results 101 to 110 of about 71,655 (241)
Discovery Radiomics via Evolutionary Deep Radiomic Sequencer Discovery for Pathologically-Proven Lung Cancer Detection [PDF]
arXiv, 2017 While lung cancer is the second most diagnosed form of cancer in men and women, a sufficiently early diagnosis can be pivotal in patient survival rates. Imaging-based, or radiomics-driven, detection methods have been developed to aid diagnosticians, but largely rely on hand-crafted features which may not fully encapsulate the differences between ...
arxiv
Radiomics as a measure superior to the Dice similarity coefficient for tumor segmentation performance evaluation [PDF]
arXiv, 2023 In high-quality radiotherapy delivery, precise segmentation of targets and healthy structures is essential. This study proposes Radiomics features as a superior measure for assessing the segmentation ability of physicians and auto-segmentation tools, in comparison to the widely used Dice Similarity Coefficient (DSC).
arxiv
Discovery Radiomics via StochasticNet Sequencers for Cancer Detection [PDF]
arXiv, 2015 Radiomics has proven to be a powerful prognostic tool for cancer detection, and has previously been applied in lung, breast, prostate, and head-and-neck cancer studies with great success. However, these radiomics-driven methods rely on pre-defined, hand-crafted radiomic feature sets that can limit their ability to characterize unique cancer traits.
arxiv
Theranostics, 2019 Medical imaging can assess the tumor and its environment in their entirety, which makes it suitable for monitoring the temporal and spatial characteristics of the tumor. Progress in computational methods, especially in artificial intelligence for medical
Zhenyu Liu +10 more
semanticscholar +1 more source
Insights into ImagingObjectives To explore the role of radiomics in predicting the prognosis of proximal esophageal cancer and to investigate the biological underpinning of radiomics in identifying different prognoses.
Linrui Li +6 more
doaj +1 more source
Sensor, Signal, and Imaging Informatics in 2017. [PDF]
, 2018 Objective To summarize significant contributions to sensor, signal, and imaging informatics literature published in 2017.Methods PubMed® and Web of Science® were searched to identify the scientific publications published in 2017 that addressed sensors ...
Deserno, Thomas M +3 more
core
Multi-Modality Information Fusion for Radiomics-based Neural Architecture Search [PDF]
arXiv, 2020 'Radiomics' is a method that extracts mineable quantitative features from radiographic images. These features can then be used to determine prognosis, for example, predicting the development of distant metastases (DM). Existing radiomics methods, however, require complex manual effort including the design of hand-crafted radiomic features and their ...
arxiv
Cancer ImagingBackground To compare the performance between one-slice two-dimensional (2D) and whole-volume three-dimensional (3D) computed tomography (CT)-based radiomics models in the prediction of lymphovascular invasion (LVI) status in esophageal squamous cell ...
Yang Li +12 more
doaj +1 more source
iScience, 2023 Summary: To guide individualized intensity-modulated radiotherapy (IMRT), we developed and prospectively validated a multiview radiomics risk model for predicting radiation-induced hypothyroidism in patients with nasopharyngeal carcinoma.
Shan-Shan Yang +8 more
doaj
SISC: End-to-end Interpretable Discovery Radiomics-Driven Lung Cancer Prediction via Stacked Interpretable Sequencing Cells [PDF]
arXiv, 2019 Objective: Lung cancer is the leading cause of cancer-related death worldwide. Computer-aided diagnosis (CAD) systems have shown significant promise in recent years for facilitating the effective detection and classification of abnormal lung nodules in computed tomography (CT) scans.
arxiv