![Loading...](https://link.springer.com/static/c4a417b97a76cc2980e3c25e2271af3129e08bbe/images/pdf-preview/spacer.gif)
-
Article
Open AccessDual-modal radiomics nomogram based on contrast-enhanced ultrasound to improve differential diagnostic accuracy and reduce unnecessary biopsy rate in ACR TI-RADS 4–5 thyroid nodules
American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS, TR) 4 and 5 thyroid nodules (TNs) demonstrate much more complicated and overlap** risk characteristics than TR1-3 and h...
-
Article
Open AccessDeep learning predicts cervical lymph node metastasis in clinically node-negative papillary thyroid carcinoma
Precise determination of cervical lymph node metastasis (CLNM) involvement in patients with early-stage thyroid cancer is fairly significant for identifying appropriate cervical treatment options. However, it ...
-
Article
A multiparametric clinic-ultrasomics nomogram for predicting extremity soft-tissue tumor malignancy: a combined retrospective and prospective bicentric study
We aimed at building and testing a multiparametric clinic-ultrasomics nomogram for prediction of malignant extremity soft-tissue tumors (ESTTs).
-
Article
Radiomics model based on shear-wave elastography in the assessment of axillary lymph node status in early-stage breast cancer
To develop and validate an ultrasound elastography radiomics nomogram for preoperative evaluation of the axillary lymph node (ALN) burden in early-stage breast cancer.
-
Article
Open AccessRole of ultrasound in the diagnosis of cervical tuberculous lymphadenitis in children
To describe sonographic characteristics of cervical tuberculous lymphadenitis (CTBL) in children, clinical information, and sonograms of 348 lymph nodes (LNs) from 57 children with CTBL were retrospectively an...
-
Article
Deep learning with convolutional neural network in the assessment of breast cancer molecular subtypes based on US images: a multicenter retrospective study
To evaluate the prediction performance of deep convolutional neural network (DCNN) based on ultrasound (US) images for the assessment of breast cancer molecular subtypes.