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Breast cancer is one of the leading diseases worldwide. According to estimates by the National Breast Cancer Foundation, over 42,000 women are expected to die from this disease in 2024.
To evaluate the predictive capabilities of MRI-based radiomics for detecting lymphovascular space invasion (LVSI) in patients diagnosed with endometrial carcinoma (EC).
The analysis of the psoas muscle in morphological and functional imaging has proved to be an accurate approach to assess sarcopenia, i.e. a systemic loss of skeletal muscle mass and function that may be correl...
Accurate detection of Hepatocellular carcinoma (HCC) feeding vessels during transcatheter arterial chemoembolization (TACE) is important for an effective treatment, while limiting non-target embolization. This...
The original article was published in BMC Medical Imaging 2024 24:192
Breast cancer prediction and diagnosis are critical for timely and effective treatment, significantly impacting patient outcomes. Machine learning algorithms have become powerful tools for improving the predic...
To evaluate early bone marrow microvascular changes in alloxan-induced diabetic rabbits using IDEAL-IQ fat quantification, texture analysis based on DCE-MRI Ktrans map, and metabolomics.
This study aims to utilize the deep learning method of VB-Net to locate and segment the trigeminal nerve, and employ radiomics methods to distinguish between CTN patients and healthy individuals.
To evaluate the prediction value of Dual-energy CT (DECT)-based quantitative parameters and radiomics model in preoperatively predicting muscle invasion in bladder cancer (BCa).
To investigate the application value of support vector machine (SVM) model based on diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE) and amide proton transfer- weighted (APTW) imaging in predi...
In recent years, as deep learning has received widespread attention in the field of heart disease, some studies have explored the potential of deep learning based on coronary angiography (CAG) or coronary CT a...
To establish a nomogram for differentiating malignant and benign focal liver lesions (FLLs) using ultrasomics features derived from contrast-enhanced ultrasound (CEUS).
Recently emerged SAM-Med2D represents a state-of-the-art advancement in medical image segmentation. Through fine-tuning the Large Visual Model, Segment Anything Model (SAM), on extensive medical datasets, it h...
To design a pulmonary ground-glass nodules (GGN) classification method based on computed tomography (CT) radiomics and machine learning for prediction of invasion in early-stage ground-glass opacity (GGO) pulm...
We aimed to probe the diagnostic value of transvaginal color Doppler ultrasound (TV-CDU) parameters in cesarean scar pregnancy (CSP) and CSP sub-types, and the relevant factors affecting patients’ surgical eff...
This systematic review aimed to evaluate the potential of deep learning algorithms for converting low-dose Positron Emission Tomography (PET) images to full-dose PET images in different body regions. A total o...
Spectral imaging of photon-counting detector CT (PCD-CT) scanners allows for generating virtual non-contrast (VNC) reconstruction. By analyzing 12 abdominal organs, we aimed to test the reliability of VNC reco...
To evaluate the clinical performance of two deep learning methods, one utilizing real clinical pairs and the other utilizing simulated datasets, in enhancing image quality for two-dimensional (2D) fast whole-b...
Radiotherapy (RT) is effective for cervical cancer but causes late side effects (SE) to nearby organs. These late SE occur more than 3 months after RT and are rated by clinical findings to determine their seve...
Develop a practical scoring system based on radiomics and imaging features, for predicting the malignant potential of incidental indeterminate small solid pulmonary nodules (IISSPNs) smaller than 20 mm.
High-Intensity Focused Ultrasound (HIFU) ablation represents a rapidly advancing non-invasive treatment modality that has achieved considerable success in addressing uterine fibroids, which constitute over 50%...
Many image fusion methods have been proposed to leverage the advantages of functional and anatomical images while compensating for their shortcomings. These methods integrate functional and anatomical images w...
Recent improvements in artificial intelligence and computer vision make it possible to automatically detect abnormalities in medical images. Skin lesions are one broad class of them. There are types of lesions...
Breast cancer is a leading cause of mortality among women globally, necessitating precise classification of breast ultrasound images for early diagnosis and treatment. Traditional methods using CNN architectur...
To investigate the value of conventional ultrasonography (US) combined with quantitative shear wave elastography (SWE) in evaluating and identifying target axillary lymph node (TALN) for fine needle aspiration...
The presence of lateral lymph node metastases (LNM) in paediatric patients with papillary thyroid cancer (PTC) is an independent risk factor for recurrence. We aimed to identify risk factors and establish a pr...
Diabetic Retinopathy (DR) and Diabetic Macular Edema (DME) are vision related complications prominently found in diabetic patients. The early identification of DR/DME grades facilitates the devising of an appr...
Although endometrial cancer (EC) is staged surgically, magnetic resonance imaging (MRI) plays a critical role in assessing and selecting the most appropriate treatment planning. We aimed to assess the diagnost...
The original article was published in BMC Medical Imaging 2024 24:144
The original article was published in BMC Medical Imaging 2024 24:172
To investigate the diagnostic value of combined 99Tcm-DX lymphoscintigraphy and CT lymphangiography (CTL) in primary chylopericardium.
To assess whether diffusion and perfusion MRI derived parameters could non-invasively predict PD-L1 and Ki-67 status in primary central nervous system diffuse large B-cell lymphoma (PCNS-DLBCL).
Non-Alcoholic Steatohepatitis (NASH) is a crucial stage in the progression of Non-Alcoholic Fatty Liver Disease(NAFLD). The purpose of this study is to explore the clinical value of ultrasound features and rad...
Pneumoconiosis has a significant impact on the quality of patient survival. This study aims to evaluate the performance and application value of improved Unet network technology in the recognition and segmenta...
Flatfoot is a condition resulting from complex three-dimensional (3D) morphological changes. Most Previous studies have been constrained by using two-dimensional radiographs and non-weight-bearing conditions. ...
Uterine fibroids are common benign tumors originating from the uterus’s smooth muscle layer, often leading to symptoms such as pelvic pain, and reproductive issues. Early detection is crucial to prevent compli...
The ratio (E/Ea) of mitral Doppler inflow velocity to annular tissue Doppler wave velocity by transthoracic echocardiography and diaphragmatic excursion (DE) by diaphragm ultrasound have been confirmed to pred...
Focal cortical dysplasia (FCD) is the most common epileptogenic developmental malformation. The diagnosis of FCD is challenging. We generated a radiomics nomogram based on multiparametric magnetic resonance im...
Due to the increasing incidence of ischaemic cerebrovascular diseases, the accurate assessment of internal carotid artery (ICA) stenosis is crucial for the development of treatment plans. This systematic revie...
In Tanzania, triphasic abdominal Computed Tomography (CT) is a more accessible and non-invasive alternative for diagnosing esophageal varices, though its accuracy has not been thoroughly evaluated, therefore t...
This study investigated potential use of computed tomography (CT)-based parameters in the lumbar spine as a surrogate for magnetic resonance imaging (MRI)-based findings.
Prostate cancer is one of the most common malignant tumors in middle-aged and elderly men and carries significant prognostic implications, and recent studies suggest that dual-energy computed tomography (DECT)...
To develop and validate a nomogram model based on Gd-EOB-DTPA enhanced MRI for differentiation between hepatocellular carcinoma (HCC) and focal nodular hyperplasia (FNH) showing iso- or hyperintensity in the h...
The early differentiation of adrenal lipid-poor adenomas from non-adenomas is a crucial step in reducing excessive examinations and treatments. This study seeks to construct an eXtreme Gradient Boosting (XGBoo...
Calculating size-specific dose estimates (SSDEs) requires measurement of the patient’s anteroposterior (AP) and lateral thickness based on computed tomography (CT) images. However, these measurements can be su...
As the quantity and significance of digital pictures in the medical industry continue to increase, Image Quality Assessment (IQA) has recently become a prevalent subject in the research community. Due to the w...
The quality of low-light endoscopic images involves applications in medical disciplines such as physiology and anatomy for the identification and judgement of tissue structures. Due to the use of point light s...
A recent global health crisis, COVID-19 is a significant global health crisis that has profoundly affected lifestyles. The detection of such diseases from similar thoracic anomalies using medical images is a c...
In order to increase the likelihood of obtaining treatment and achieving a complete recovery, early illness identification and diagnosis are crucial. Artificial intelligence is helpful with this process by all...
Computed tomography (CT) is widely in clinics and is affected by metal implants. Metal segmentation is crucial for metal artifact correction, and the common threshold method often fails to accurately segment m...
Citation Impact 2023
Journal Impact Factor: 2.9
5-year Journal Impact Factor: 2.8
Source Normalized Impact per Paper (SNIP): 1.157
SCImago Journal Rank (SJR): 0.701
Speed 2023
Submission to first editorial decision (median days): 13
Submission to acceptance (median days): 177
Usage 2023
Downloads: 951,496
Altmetric mentions: 161
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