SynthesisJournal of ultrasound2024
A systematic review of machine learning based thyroid tumor characterisation using ultrasonographic images.
Synthesis in Journal of ultrasound, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 26 citations in OpenAlex.
- DLoG - automatic disc based laplacian of gaussian operator for carotid artery boundary extraction in ultrasound images.Scientific reports · 2026Article
- Deep learning-based classification of thyroid nodules using uncertainty-aware multi-modal ultrasound imaging.Scientific reports · 2026Article
- Deep learning based on ultrasound for differential diagnosis of pancreatic serous cystic neoplasm and mucinous cystic neoplasm.BMC cancer · 2025Article
- From pretraining to privacy: federated ultrasound foundation model with self-supervised learning.NPJ digital medicine · 2025Article
- Malignancy prediction for calcified thyroid nodules using deep learning based on ultrasound dynamic videos.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- An interpretable multimodal machine learning model for predicting malignancy of thyroid nodules in low-resource scenarios.BMC endocrine disorders · 2025Article
- Combining curriculum learning and weakly supervised attention for enhanced thyroid nodule assessment in ultrasound imaging.Quantitative imaging in medicine and surgery · 2025Article
- A weakly-supervised follicle segmentation method in ultrasound images.Scientific reports · 2025Article
- Predicting the efficacy of microwave ablation of benign thyroid nodules from ultrasound images using deep convolutional neural networks.BMC medical informatics and decision making · 2025Article
- Computer-aided diagnosis of hepatic cystic echinococcosis based on deep transfer learning features from ultrasound images.Scientific reports · 2025Article
- Identification of lesion location and discrimination between benign and malignant findings in thyroid ultrasound imaging.Scientific reports · 2024Article
- Deep learning based binary classification of diabetic retinopathy images using transfer learning approach.Journal of diabetes and metabolic disorders · 2024Article
- Performance of ACR-TIRADS in assessing thyroid nodules does not vary according to patient age.Hormones (Athens, Greece) · 2024Article
- CystNet: An AI driven model for PCOS detection using multilevel thresholding of ultrasound images.Scientific reports · 2024Article
- Role of inter- and extra-lesion tissue, transfer learning, and fine-tuning in the robust classification of breast lesions.Scientific reports · 2024Article
- Revolutionizing breast ultrasound diagnostics with EfficientNet-B7 and Explainable AI.BMC medical imaging · 2024Article
- Diagnostic value of an interpretable machine learning model based on clinical ultrasound features for follicular thyroid carcinoma.Quantitative imaging in medicine and surgery · 2024Article
- Spatial and geometric learning for classification of breast tumors from multi-center ultrasound images: a hybrid learning approach.BMC medical imaging · 2024Article
- Automatic segmentation of 15 critical anatomical labels and measurements of cardiac axis and cardiothoracic ratio in fetal four chambers using nnU-NetV2.BMC medical informatics and decision making · 2024Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ultrasonography is widely used to screen thyroid tumors because it is safe, easy to use, and low-cost. However, it is simultaneously affected by speckle noise and other artifacts, so early detection of thyroid abnormalities becomes difficult for the radiologist. Therefore, various researchers continuously address the limitations of sonography and improve the diagnosis potential of US images for thyroid tissue from the last three decays. Accordingly, the present study extensively reviewed various CAD systems used to classify thyroid tumor US (TTUS) images related to datasets, despeckling algorithms, segmentation algorithms, feature extraction and selection, assessment parameters, and classification algorithms. After the exhaustive review, the achievements and challenges have been reported, and build a road map for the new researchers.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.