Purpose Attenuation correction and scatter compensation (AC/SC) are two main steps
toward quantitative PET imaging, which remain challenging in PET-only and PET/MRI …

Background Use of adjuvant chemotherapy in patients with early-stage lung cancer is
controversial because no definite biomarker exists to identify patients who would receive …

Abstract Non-Small Cell Lung Cancer (NSCLC) is a major lung cancer type. Proper
diagnosis depends mainly on tumor staging and grading. Pathological prognosis often faces …

Deep learning (DL) is a breakthrough technology for medical imaging with high sample size
requirements and interpretability issues. Using a pretrained DL model through a radiomics …

The aim of this study was to investigate the usefulness of radiomics in the absence of well-
defined standard guidelines. Specifically, we extracted radiomics features from multicenter …

In this work, we study the problem of clustering survival data $-$ a challenging and so far
under-explored task. We introduce a novel semi-supervised probabilistic approach to cluster …

Purpose A large chunk of lung cancers are of the type non-small cell lung cancer (NSCLC).
Both the treatment planning and patients' prognosis depend greatly on factors like AJCC …

Purpose To identify the optimal mother wavelets in survival prediction of lung cancer
patients using wavelet decomposition‐based (WDB) radiomic features in CT images …

Background Robust imaging biomarkers are needed for risk stratification in stage I lung
adenocarcinoma patients in order to select optimal treatment regimen. We aimed to …

Background Histologic phenotype identification of Non-Small Cell Lung Cancer (NSCLC) is
essential for treatment planning and prognostic prediction. The prediction model based on …