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To explore the value of multiparametric MRI markers for preoperative prediction of Ki-67 expression among patients with rectal cancer.
To investigate the association between CT signs and clinicopathological features and disease recurrence in patients with hepatoid adenocarcinoma of stomach (HAS).
We aimed to perform a qualitative synthesis of evidence on the role of 68Ga-Pentixafor PET in atherosclerosis.
Diagnosis of small airway disease on computed tomography (CT) scans is challenging in patients with a history of chemical warfare exposure. We developed a software package based on different methodologies to i...
This study evaluated the radiologic and radiomic features extracted from magnetic resonance imaging (MRI) in meningioma after radiation therapy and investigated the impact of radiation therapy in treating meni...
Parameters, such as left ventricular ejection fraction, peak strain dispersion, global longitudinal strain, etc. are influential and clinically interpretable for detection of cardiac disease, while manual dete...
The deterministic deep learning models have achieved state-of-the-art performance in various medical image analysis tasks, including nuclei segmentation from histopathology images. The deterministic models foc...
This study was to prospectively investigate the feasibility of four-dimensional computed tomography angiography (4D-CTA) with electrocardiogram-gated (ECG) reconstruction for preoperative evaluation of morphol...
CT-guided radiofrequency ablation (RFA) is among the thermal ablative procedures and provides great benefits with a minimally invasive procedure. In this prospective study, we aimed to reveal the significance ...
There is a paucity of research investigating the application of machine learning techniques for distinguishing between lipid-poor adrenal adenoma (LPA) and subclinical pheochromocytoma (sPHEO) based on radiomi...
The hippocampus is a key area of the brain responsible for learning, memory, and other abilities. Accurately segmenting the hippocampus and precisely calculating the volume of the hippocampus is of great signi...
The original article was published in BMC Medical Imaging 2023 23:147
Accurate grading of semantic characteristics is helpful for radiologists to determine the probabilities of the likelihood of malignancy of a pulmonary nodule. Nevertheless, because of the complex and varied pr...
Infiltrating tumor border configuration (iTBC) is assessed by postoperative pathological examination, thus, is not helpful for preoperative treatment strategies. The study aimed to detect iTBC by magnetic reso...
Several machine learning (ML) classifiers for thyroid nodule diagnosis have been compared in terms of their accuracy, sensitivity, specificity, negative predictive value (NPV), positive predictive value (PPV),...
Cervical cancer patients receiving radiotherapy and chemotherapy require accurate survival prediction methods. The objective of this study was to develop a prognostic analysis model based on a radiomics score ...
This study evaluated the prevalence and types of intracranial lesions through dedicated imaging analysis of primary headaches in children and compared them between patients with and without migraine.
The safety and efficacy of 17-gauge needles used in CT-guided percutaneous cryoablation for lung nodules were explored in this study. The purpose of the study was to compare the findings with earlier research ...
Medical images such as CT and X-ray have been widely used for the detection of several chest infections and lung diseases. However, these images are susceptible to different types of noise, and it is hard to r...
To explore the feasibility of low-dose computed tomography (LDCT) with asynchronous quantitative computed tomography (asynchronous QCT) for assessing the volumetric bone mineral density (vBMD).
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...
The Correction to this article has been published in BMC Medical Imaging 2023 23:157
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...
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)
2023 Speed
34 days submission to first editorial decision for all manuscripts (Median)
177 days submission to accept (Median)
2023 Usage
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