HTC-Net: Hashimoto’s thyroiditis ultrasound image classification model based on residual network reinforced by channel attention mechanism

Zhang, Liang; Chen, Kang; Luo, T.; Jiang, Wenchao; Wen, Jian-cong; Zhao, Ling; Song, Wei

doi:10.1007/s13755-023-00225-y

Cited by 5 publications

(2 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…21 This application involves feeding the model with preprocessed US images and receiving the corresponding classification results, including the probability of HT. 22 The implementation of an automated classification algorithm holds immense potential for enhancing the efficiency and accuracy of HT assessment. Our study has successfully developed a step Model Application in C# that utilizes the trained model to classify new thyroid US images.…”

Section: Discussionmentioning

confidence: 99%

Automated Thyroid Ultrasound Analysis: Hashimoto’s Thyroiditis

de Oliveira Andrade,

de Oliveira,

de Oliveira

et al. 2024

Preprint

View full text Add to dashboard Cite

Introduction: Thyroid ultrasound provides valuable insights for thyroid disorders but is hampered by subjectivity. Automated analysis utilizing large datasets holds immense promise for objective and standardized assessment in screening, thyroid nodule classification, and treatment monitoring. However, there remains a significant gap in the development of applications for the automated analysis of Hashimoto's thyroiditis (HT) using ultrasound. Objective: To develop an automated thyroid ultrasound analysis (ATUS) algorithm using the C# programming language to detect and quantify ultrasonographic characteristics associated with HT. Materials and Methods: This study describes the development and evaluation of an ATUS algorithm using C#. The algorithm extracte relevant features (texture, vascularization, echogenicity) from preprocessed ultrasound images and utilizes machine learning techniques to classify them as "normal" or indicative of HT. The model is trained and validated on a comprehensive dataset, with performance assessed through metrics like accuracy, sensitivity, and specificity. The findings highlight the potential for this C#-based ATUS algorithm to offer objective and standardized assessment for HT diagnosis. Results: The program preprocesses images (grayscale conversion, normalization, etc.), segments the thyroid region, extracts features (texture, echogenicity), and utilizes a pre-trained model for classification ("normal" or "suspected Hashimoto's thyroiditis"). Using a sample image, the program successfully preprocessed, segmented, and extracted features. The predicted classification ("suspected HT") with high probability (0.92) aligns with the pre-established diagnosis, suggesting potential for objective HT assessment. Conclusion: C#-based ATUS algorithm successfully detects and quantifies Hashimoto's thyroiditis features, showcasing the potential of advanced programming in medical image analysis. Keywords: Automated Thyroid Ultrasound Analysis, Hashimoto's Thyroiditis, C# programming language.

show abstract

Section: Discussionmentioning

confidence: 99%

Automated Thyroid Ultrasound Analysis: Hashimoto’s Thyroiditis

de Oliveira Andrade,

de Oliveira,

de Oliveira

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…Diagnosis of HT is established based on a range of clinical signs and symptoms and the presence of serum thyroid antibodies, thyroperoxidase, and thyroglobulin [ 3 ]. Ultrasound examination is the most common imaging modality in patients with thyroid disease, with its utility reported for both diagnostic and interventional purposes [ 11 ].…”

Section: Discussionmentioning

confidence: 99%

Hashimoto’s Thyroiditis Presenting As Non-specific Low Back Pain: A Case Report on Diagnostic Challenges and Management in Primary Care

Annison,

Abedi,

Mansfield

2024

Cureus

View full text Add to dashboard Cite

Non-specific low back pain (NSLBP) may account for 90-95% of cases of low back pain presenting to primary care. Clinicians should remain vigilant however to non-spinal musculoskeletal conditions that may mimic NSLBP and musculoskeletal complaints. We present a case of a 38-year-old female with low back pain, lower limb tightness, groin pain, and leg cramps. Symptoms failed to improve with physiotherapy and subsequent blood tests revealed elevated thyroid-stimulating hormone (TSH), and elevated thyroid peroxidase antibody (TPO). The patient was diagnosed with hypothyroidism secondary to Hashimoto's thyroiditis (HT), an autoimmune endocrine thyroid disorder. Levothyroxine 100 microgram(µg) was prescribed, and clinical symptoms improved within eight weeks. Clinicians may wish to consider thyroid dysfunction when patients with common musculoskeletal complaints, weight gain, and fatigue respond atypically to evidence-based physiotherapy management.

show abstract