The full-iterative model reconstruction generates ultra-high-resolution computed tomography (U-HRCT) images comprising a 1024 × 1024 matrix and 0.25 mm thickness while suppressing image noises, allowing evaluating small airways 1-2 mm in diameter. Ho...
BACKGROUND: With the rapid spread of COVID-19 worldwide, quick screening for possible COVID-19 patients has become the focus of international researchers. Recently, many deep learning-based Computed Tomography (CT) image/X-ray image fast screening mo...
Subarachnoid hemorrhage (SAH) is one of the critical and severe neurological diseases with high morbidity and mortality. Head computed tomography (CT) is among the preferred methods for the diagnosis of SAH, which is confirmed by CT showing high-dens...
European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Nov 19, 2021
OBJECTIVE: To evaluate the performance of a deep learning (DL)-based radiomics strategy on contrast-enhanced computed tomography (CT) to predict microvascular invasion (MVI) status and clinical outcomes, recurrence-free survival (RFS) and overall sur...
The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association
Nov 17, 2021
OBJECTIVE: Several severity metrics have been developed for metopic craniosynostosis, including a recent machine learning-derived algorithm. This study assessed the diagnostic concordance between machine learning and previously published severity ind...
PURPOSE: Deep learning-based image denoising and reconstruction methods demonstrated promising performance on low-dose CT imaging in recent years. However, most existing deep learning-based low-dose CT reconstruction methods require normal-dose image...
In current clinical practice, tumor response assessment is usually based on tumor size change on serial computerized tomography (CT) scan images. However, evaluation of tumor response to anti-vascular endothelial growth factor therapies in metastatic...
BACKGROUND: Accurate target volume delineation is a prerequisite for high-precision radiotherapy. However, manual delineation is resource-demanding and prone to interobserver variation. An automatic delineation approach could potentially save time an...
Physical and engineering sciences in medicine
Nov 15, 2021
COVID-19 is an infectious disease, which has adversely affected public health and the economy across the world. On account of the highly infectious nature of the disease, rapid automated diagnosis of COVID-19 is urgently needed. A few recent findings...
OBJECTIVE: To develop and validate a deep learning nomogram (DLN) model constructed from non-contrast computed tomography (CT) images for discriminating minimally invasive adenocarcinoma (MIA) from invasive adenocarcinoma (IAC) in patients with subso...
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