Page 1 of 27
During the acquisition of MRI data, patient-, sequence-, or hardware-related factors can introduce artefacts that degrade image quality. Four of the most significant tasks for improving MRI image quality have ...
This study aimed to develop and validate radiomics models on the basis of computed tomography (CT) and clinical features for the prediction of pulmonary metastases (MT) in patients with Ewing sarcoma (ES) with...
COVID-19, the global pandemic of twenty-first century, has caused major challenges and setbacks for researchers and medical infrastructure worldwide. The CoVID-19 influences on the patients respiratory system ...
Radical concurrent chemoradiotherapy (CCRT) is frequently used as the first-line treatment for patients with locally advanced esophageal cancer. Unfortunately, some patients respond poorly. To predict response...
This study seeks to evaluate the value of MRI (Magnetic resonance imaging) diffusion weighted images (DWI), diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) in the diagnosis of cervical...
A manual evaluation of the CI electrode position from CT and DVT scans may be affected by diagnostic errors due to cognitive biases. The aim of this study was to compare the CI electrode localization using an ...
Accurately segmenting the hippocampus is an essential step in brain tumor radiotherapy planning. Some patients undergo brain tumor resection beforehand, which can significantly alter the postoperative regions’...
The WHO grade and Ki-67 index are independent indices used to evaluate the malignant biological behavior of meningioma. This study aims to develop MRI-based machine learning models to predict the malignant bio...
Artificial intelligence has been widely investigated for diagnosis and treatment strategy design, with some models proposed for detecting oral pharyngeal, nasopharyngeal, or laryngeal carcinoma. However, no co...
Accurate preoperative fistula diagnostics in male anorectal malformations (ARM) after colostomy are of great significance. We reviewed our institutional experiences and explored methods for improving the preop...
This study aimed to develop a computed tomography (CT) model to predict Ki-67 expression in hepatocellular carcinoma (HCC) and to examine the added value of radiomics to clinico-radiological features.
Cervical cell segmentation is a fundamental step in automated cervical cancer cytology screening. The aim of this study was to develop and evaluate a deep ensemble model for cervical cell segmentation includin...
To investigate the brain structural correlates of postoperative axial pain (PAP) in degenerative cervical myelopathy (DCM) following posterior cervical decompression surgery.
Whether there is axillary lymph node metastasis is crucial for formulating the treatment plan for breast cancer. Currently, invasive methods are still used for preoperative evaluation of lymph nodes. If non-in...
Continuous release of image databases with fully or partially identical inner categories dramatically deteriorates the production of autonomous Computer-Aided Diagnostics (CAD) systems for true comprehensive m...
Registration of three-dimensional (3D) knee implant components to radiographic images provides the 3D position of the implants which aids to analyze the component alignment after total knee arthroplasty.
Accurate diagnosis of breast cancer (BC) plays a crucial role in clinical pathology analysis and ensuring precise surgical margins to prevent recurrence.
To identify CT features and establish a nomogram, compared with a machine learning-based model for distinguishing gastrointestinal heterotopic pancreas (HP) from gastrointestinal stromal tumor (GIST).
The usefulness of endometrium strain elastosonography (SE) for the evaluation of endometrial receptivity in women undergoing in vitro fertilization (IVF) remains controversial. The objective of this prospectiv...
Vision transformer-based methods are advancing the field of medical artificial intelligence and cancer imaging, including lung cancer applications. Recently, many researchers have developed vision transformer-...
Bronchogenic cysts (BCs) are rare and usually asymptomatic malformations detected during imaging examinations. We aimed to investigate the clinical and imaging characteristics of patients with BCs.
In studies of the association of adiposity with disease risk, widely used anthropometric measures of adiposity (e.g. body-mass-index [BMI], waist circumference [WC], waist-hip ratio [WHR]) are simple and inexp...
Hybrid quantum systems have shown promise in image classification by combining the strengths of both classical and quantum algorithms. These systems leverage the parallel processing power of quantum computers ...
The purpose of this study was to determine whether radiological measurements of radial fracture position made in cone beam computed tomography (CBCT) projection images are comparable to those made on tradition...
Brain extraction is an essential prerequisite for the automated diagnosis of intracranial lesions and determines, to a certain extent, the accuracy of subsequent lesion recognition, location, and segmentation....
This study constructed a nomogram based on grayscale ultrasound features and real-time shear wave elastography (SWE) parameters to predict thyroid cancer.
To compare the inter-modality consistency and diagnostic performances of the contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) and contrast-enhanced computed tomography (CEC...
Few studies have explored the clinical feasibility of using deep-learning reconstruction to reduce the radiation dose of CT. We aimed to compare the image quality and lung nodule detectability between chest CT...
To develop a fully automated CNN detection system based on magnetic resonance imaging (MRI) for ACL injury, and to explore the feasibility of CNN for ACL injury detection on MRI images.
To investigate the diagnostic performance of parameters derived from monoexponential, biexponential, and stretched-exponential diffusion-weighted imaging models in differentiating tumour progression from pseud...
To predict ductal carcinoma in situ with microinvasion (DCISMI) based on clinicopathologic, conventional breast magnetic resonance imaging (MRI), and dynamic contrast enhanced MRI (DCE-MRI) radiomics signature...
Acute closed volar plate injury of the proximal interphalangeal joint (PIP) is a common hand injury. In the past, there were few objective evaluation imaging methods for the degree of volar plate injury. The p...
Differentiating between low-grade glioma and brain glial cell hyperplasia is crucial for the customized clinical treatment of patients.
Incidental thymus region masses during thoracic examinations are not uncommon. The clinician’s decision-making for treatment largely depends on imaging findings. Due to the lack of specific indicators, it may ...
In recent years, contrast-enhanced ultrasonography (CEUS) has been used for various applications in breast diagnosis. The superiority of CEUS over conventional B-mode imaging in the ultrasound diagnosis of the...
This study aimed to develop and validate a deep learning-based method that detects inter-breath-hold motion from an estimated cardiac long axis image reconstructed from a stack of short axis cardiac cine images.
On the basis of visual-dependent reading method, radiological recognition and assessment of neonatal hyperbilirubinemia (NH) or acute bilirubin encephalopathy (ABE) on conventional magnetic resonance imaging (...
To build a combined model based on the ultrasound radiomic and morphological features, and evaluate its diagnostic performance for preoperative prediction of central lymph node metastasis (CLNM) in patients wi...
Spectral CT imaging parameters have been reported to be useful in the differentiation of pathological grades in different malignancies. This study aims to investigate the value of spectral CT in the quantitati...
Dental film mounting is an essential but time-consuming task in dental radiography, with manual methods often prone to errors. This study aims to develop a deep learning (DL) model for accurate automated class...
To develop a quantitative analysis method for right diaphragm deformation. This method is based on optical flow and applied to diaphragm ultrasound imaging.
To assess the predictive values of primary tumor FDG uptake for patients with inoperable stage III non-small cell lung cancer (NSCLC) after concurrent chemoradiotherapy (CCRT).
Biparametric MRI (bpMRI) is a faster, contrast-free, and less expensive MRI protocol that facilitates the detection of prostate cancer. The aim of this study is to determine whether a biparametric MRI PI-RADS ...
Pulmonary sarcomatoid carcinoma (PSC) is a rare subtype of non-small cell lung cancer (NSCLC) but differs in terms of treatment strategies compared with conventional-NSCLC (c-NSCLC). However, preoperative CT d...
In this work, we propose a processing pipeline for the extraction and identification of meaningful radiomics biomarkers in skeletal muscle tissue as displayed using Dixon-weighted MRI. Diverse and robust radio...
The aim of this study was to explore application value of iodine concentration from dual-energy spectral computed tomography (DESCT) in preoperative prediction of lymphovascular tumor thrombus in patients with...
Megavoltage computed tomography (MVCT) images acquired during each radiotherapy session may be useful for delta radiomics. However, no studies have examined whether the MVCT-based radiomics has prognostic powe...
Lymph node metastasis is an important factor affecting the treatment and prognosis of patients with cervical cancer. However, the comparison of different algorithms and features to predict lymph node metastasi...
Retinal vessel segmentation provides an important basis for determining the geometric characteristics of retinal vessels and the diagnosis of related diseases. The retinal vessels are mainly composed of coarse...
Sinonasal rhabdomyosarcoma (RMS) in adults is extremely rare, and early diagnosis and treatment are crucial to improve the patient’s prognosis. The purpose of this study was to evaluate the magnetic resonance ...
2022 Citation Impact
2.7 - 2-year Impact Factor
2.7 - 5-year Impact Factor
0.983 - SNIP (Source Normalized Impact per Paper)
0.535 - SJR (SCImago Journal Rank)
2022 Speed
26 days submission to first editorial decision for all manuscripts (Median)
144 days submission to accept (Median)
2022 Usage
739,122 downloads
329 Altmetric mentions
The following summary describes the peer review process for this journal:
Identity transparency: Single anonymized
Reviewer interacts with: Editor
Review information published: Review reports. Reviewer Identities reviewer opt in. Author/reviewer communication