AIMC Topic: Ultrasonography

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Towards robust multimodal ultrasound classification for liver tumor diagnosis: A generative approach to modality missingness.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In medical image analysis, combining multiple imaging modalities enhances diagnostic accuracy by providing complementary information. However, missing modalities are common in clinical settings, limiting the effectiveness of...

ChatGPT-4's Accuracy in Estimating Thyroid Nodule Features and Cancer Risk From Ultrasound Images.

Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists
OBJECTIVE: To evaluate the performance of GPT-4 and GPT-4o in accurately identifying features and categories from thyroid nodule ultrasound images following the American College of Radiology Thyroid Imaging Reporting and Data System (TI-RADS).

Deep learning based on ultrasound images predicting cervical lymph node metastasis in postoperative patients with differentiated thyroid carcinoma.

The British journal of radiology
OBJECTIVES: To develop a deep learning (DL) model based on ultrasound (US) images of lymph nodes for predicting cervical lymph node metastasis (CLNM) in postoperative patients with differentiated thyroid carcinoma (DTC).

Coarse for Fine: Bounding Box Supervised Thyroid Ultrasound Image Segmentation Using Spatial Arrangement and Hierarchical Prediction Consistency.

IEEE journal of biomedical and health informatics
Weakly-supervised learning methods have become increasingly attractive for medical image segmentation, but suffered from a high dependence on quantifying the pixel-wise affinities of low-level features, which are easily corrupted in thyroid ultrasoun...

Advancing Acoustic Droplet Vaporization for Tissue Characterization Using Quantitative Ultrasound and Transfer Learning.

IEEE transactions on bio-medical engineering
Acoustic droplet vaporization (ADV) is an emerging technique with expanding applications in biomedical ultrasound. ADV-generated bubbles can function as microscale probes that provide insights into the mechanical properties of their surrounding micro...

Deep learning based motion correction in ultrasound microvessel imaging approach improves thyroid nodule classification.

Scientific reports
To address inter-frame motion artifacts in ultrasound quantitative high-definition microvasculature imaging (qHDMI), we introduced a novel deep learning-based motion correction technique. This approach enables the derivation of more accurate quantita...

Prediction of clinical stages of cervical cancer via machine learning integrated with clinical features and ultrasound-based radiomics.

Scientific reports
To investigate the prediction of a model constructed by combining machine learning (ML) with clinical features and ultrasound radiomics in the clinical staging of cervical cancer. General clinical and ultrasound data of 227 patients with cervical can...

Differentiation of canine and feline neoplasms using multi-modal imaging and machine learning.

Scientific reports
Canine/feline (sub-)cutaneous tumors, which include lipomas, mastocytomas and soft tissue sarcomas, introduce diagnostic challenges due to inherent tissue heterogeneity, accompanied by diverse clinical pathogenesis. Current study integrates conventio...

Multimodal ultrasound-based radiomics and deep learning for differential diagnosis of O-RADS 4-5 adnexal masses.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Accurate differentiation between benign and malignant adnexal masses is crucial for patients to avoid unnecessary surgical interventions. Ultrasound (US) is the most widely utilized diagnostic and screening tool for gynecological diseases...

Recognizing artery segments on carotid ultrasonography using embedding concatenation of deep image and vision-language models.

Physics in medicine and biology
Evaluating large artery atherosclerosis is critical for predicting and preventing ischemic strokes. Ultrasonographic assessment of the carotid arteries is the preferred first-line examination due to its ease of use, noninvasive, and absence of radiat...