Literature DB >> 24206204

A review on ultrasound-based thyroid cancer tissue characterization and automated classification.

U R Acharya1, G Swapna, S V Sree, F Molinari, S Gupta, R H Bardales, A Witkowska, J S Suri.   

Abstract

In this paper, we review the different studies that developed Computer Aided Diagnostic (CAD) for automated classification of thyroid cancer into benign and malignant types. Specifically, we discuss the different types of features that are used to study and analyze the differences between benign and malignant thyroid nodules. These features can be broadly categorized into (a) the sonographic features from the ultrasound images, and (b) the non-clinical features extracted from the ultrasound images using statistical and data mining techniques. We also present a brief description of the commonly used classifiers in ultrasound based CAD systems. We then review the studies that used features based on the ultrasound images for thyroid nodule classification and highlight the limitations of such studies. We also discuss and review the techniques used in studies that used the non-clinical features for thyroid nodule classification and report the classification accuracies obtained in these studies.

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Mesh:

Year:  2013        PMID: 24206204     DOI: 10.7785/tcrt.2012.500381

Source DB:  PubMed          Journal:  Technol Cancer Res Treat        ISSN: 1533-0338


  25 in total

1.  Wilson disease tissue classification and characterization using seven artificial intelligence models embedded with 3D optimization paradigm on a weak training brain magnetic resonance imaging datasets: a supercomputer application.

Authors:  Mohit Agarwal; Luca Saba; Suneet K Gupta; Amer M Johri; Narendra N Khanna; Sophie Mavrogeni; John R Laird; Gyan Pareek; Martin Miner; Petros P Sfikakis; Athanasios Protogerou; Aditya M Sharma; Vijay Viswanathan; George D Kitas; Andrew Nicolaides; Jasjit S Suri
Journal:  Med Biol Eng Comput       Date:  2021-02-05       Impact factor: 2.602

2.  Computer-aided diagnosis of malignant or benign thyroid nodes based on ultrasound images.

Authors:  Qin Yu; Tao Jiang; Aiyun Zhou; Lili Zhang; Cheng Zhang; Pan Xu
Journal:  Eur Arch Otorhinolaryngol       Date:  2017-04-07       Impact factor: 2.503

3.  Multiclass machine learning vs. conventional calculators for stroke/CVD risk assessment using carotid plaque predictors with coronary angiography scores as gold standard: a 500 participants study.

Authors:  Ankush D Jamthikar; Deep Gupta; Laura E Mantella; Luca Saba; John R Laird; Amer M Johri; Jasjit S Suri
Journal:  Int J Cardiovasc Imaging       Date:  2020-11-12       Impact factor: 2.357

4.  Effect of Watermarking on Diagnostic Preservation of Atherosclerotic Ultrasound Video in Stroke Telemedicine.

Authors:  Nilanjan Dey; Soumyo Bose; Achintya Das; Sheli Sinha Chaudhuri; Luca Saba; Shoaib Shafique; Andrew Nicolaides; Jasjit S Suri
Journal:  J Med Syst       Date:  2016-02-10       Impact factor: 4.460

Review 5.  Multimodality carotid plaque tissue characterization and classification in the artificial intelligence paradigm: a narrative review for stroke application.

Authors:  Luca Saba; Skandha S Sanagala; Suneet K Gupta; Vijaya K Koppula; Amer M Johri; Narendra N Khanna; Sophie Mavrogeni; John R Laird; Gyan Pareek; Martin Miner; Petros P Sfikakis; Athanasios Protogerou; Durga P Misra; Vikas Agarwal; Aditya M Sharma; Vijay Viswanathan; Vijay S Rathore; Monika Turk; Raghu Kolluri; Klaudija Viskovic; Elisa Cuadrado-Godia; George D Kitas; Neeraj Sharma; Andrew Nicolaides; Jasjit S Suri
Journal:  Ann Transl Med       Date:  2021-07

6.  Analysis of the Application Value of Ultrasound Imaging Diagnosis in the Clinical Staging of Thyroid Cancer.

Authors:  Fengying Zhang; Yunxuan Sun; Xijiang Wu; Chunrong Meng; Meiling Xiang; Tingting Huang; Wenping Duan; Fangfang Wang; Zhaolan Sun
Journal:  J Oncol       Date:  2022-06-08       Impact factor: 4.501

Review 7.  Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/Non-COVID-19 Frameworks Using Artificial Intelligence Paradigm: A Narrative Review.

Authors:  Smiksha Munjral; Mahesh Maindarkar; Puneet Ahluwalia; Anudeep Puvvula; Ankush Jamthikar; Tanay Jujaray; Neha Suri; Sudip Paul; Rajesh Pathak; Luca Saba; Renoh Johnson Chalakkal; Suneet Gupta; Gavino Faa; Inder M Singh; Paramjit S Chadha; Monika Turk; Amer M Johri; Narendra N Khanna; Klaudija Viskovic; Sophie Mavrogeni; John R Laird; Gyan Pareek; Martin Miner; David W Sobel; Antonella Balestrieri; Petros P Sfikakis; George Tsoulfas; Athanasios Protogerou; Durga Prasanna Misra; Vikas Agarwal; George D Kitas; Raghu Kolluri; Jagjit Teji; Mustafa Al-Maini; Surinder K Dhanjil; Meyypan Sockalingam; Ajit Saxena; Aditya Sharma; Vijay Rathore; Mostafa Fatemi; Azra Alizad; Vijay Viswanathan; Padukode R Krishnan; Tomaz Omerzu; Subbaram Naidu; Andrew Nicolaides; Mostafa M Fouda; Jasjit S Suri
Journal:  Diagnostics (Basel)       Date:  2022-05-14

8.  Convolutional Neural Network to Stratify the Malignancy Risk of Thyroid Nodules: Diagnostic Performance Compared with the American College of Radiology Thyroid Imaging Reporting and Data System Implemented by Experienced Radiologists.

Authors:  G R Kim; E Lee; H R Kim; J H Yoon; V Y Park; J Y Kwak
Journal:  AJNR Am J Neuroradiol       Date:  2021-05-13       Impact factor: 4.966

9.  Thyroid Nodule Classification in Ultrasound Images by Fine-Tuning Deep Convolutional Neural Network.

Authors:  Jianning Chi; Ekta Walia; Paul Babyn; Jimmy Wang; Gary Groot; Mark Eramian
Journal:  J Digit Imaging       Date:  2017-08       Impact factor: 4.056

10.  Computer-aided diagnosis system of thyroid nodules ultrasonography: Diagnostic performance difference between computer-aided diagnosis and 111 radiologists.

Authors:  Tingting Li; Zirui Jiang; Man Lu; Shibin Zou; Minggang Wu; Ting Wei; Lu Wang; Juan Li; Ziyue Hu; Xueqing Cheng; Jifen Liao
Journal:  Medicine (Baltimore)       Date:  2020-06-05       Impact factor: 1.817

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