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Open AccessPET/CT deep learning prognosis for treatment decision support in esophageal squamous cell carcinoma
The clinical decision-making regarding choosing surgery alone (SA) or surgery followed by postoperative adjuvant chemotherapy (SPOCT) in esophageal squamous cell carcinoma (ESCC) remains controversial. We aim ...
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Article
Open AccessEfficientNet-Based System for Detecting EGFR-Mutant Status and Predicting Prognosis of Tyrosine Kinase Inhibitors in Patients with NSCLC
We aimed to develop and validate a deep learning-based system using pre-therapy computed tomography (CT) images to detect epidermal growth factor receptor (EGFR)-mutant status in patients with non-small cell l...
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Article
Intratumoral and Peritumoral Analysis of Mammography, Tomosynthesis, and Multiparametric MRI for Predicting Ki-67 Level in Breast Cancer: a Radiomics-Based Study
To noninvasively evaluate the use of intratumoral and peritumoral regions from full-field digital mammography (DM), digital breast tomosynthesis (DBT), dynamic contrast-enhanced (DCE), and diffusion-weighted (...
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Article
Open AccessDecoding intra-tumoral spatial heterogeneity on radiological images using the Hilbert curve
Current intra-tumoral heterogeneous feature extraction in radiology is limited to the use of a single slice or the region of interest within a few context-associated slices, and the decoding of intra-tumoral s...
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Article
Correction to: End-to-end automatic differentiation of the coronavirus disease 2019 (COVID-19) from viral pneumonia based on chest CT
A Correction to this paper has been published: https://doi.org/10.1007/s00259-021-05267-6
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Article
Correction to: Decoding COVID-19 pneumonia: comparison of deep learning and radiomics CT image signatures
A Correction to this paper has been published: https://doi.org/10.1007/s00259-021-05268-5
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Article
Open AccessDecoding COVID-19 pneumonia: comparison of deep learning and radiomics CT image signatures
High-dimensional image features that underlie COVID-19 pneumonia remain opaque. We aim to compare feature engineering and deep learning methods to gain insights into the image features that drive CT-based for ...
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Article
Open AccessEnd-to-end automatic differentiation of the coronavirus disease 2019 (COVID-19) from viral pneumonia based on chest CT
In the absence of a virus nucleic acid real-time reverse transcriptase-polymerase chain reaction (RT-PCR) test and experienced radiologists, clinical diagnosis is challenging for viral pneumonia with clinical ...
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Article
Open AccessDevelopment and validation of a prognostic index for efficacy evaluation and prognosis of first-line chemotherapy in stage III–IV lung squamous cell carcinoma
To establish a pre-therapy prognostic index model (PIM) of the first-line chemotherapy aiming to achieve accurate prediction of time to progression (TTP) and overall survival among the patients diagnosed with ...
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Article
Radiomic signature as a diagnostic factor for histologic subtype classification of non-small cell lung cancer
To distinguish squamous cell carcinoma (SCC) from lung adenocarcinoma (ADC) based on a radiomic signature
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Chapter
Radiomics in Medical Imaging—Detection, Extraction and Segmentation
Radiomics, as a newly emerging technology, converts medical images into high-dimensional data via high-throughput extraction of quantitative features, followed by subsequent data analysis for decision support....
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Article
Open AccessNon-small cell lung cancer: quantitative phenotypic analysis of CT images as a potential marker of prognosis
This was a retrospective study to investigate the predictive and prognostic ability of quantitative computed tomography phenotypic features in patients with non-small cell lung cancer (NSCLC). 661 patients wit...
