A Simple Method for 3D Thyroid Reconstruction from 2D Ultrasound Slices

Ciora, Radu Adrian; Neamţu, B.V.; Sofariu, Ciprian; Dospinescu, Cristina; Barbu, Andreea; Banciu, Daniel Dumitriu

doi:10.1109/ehb47216.2019.8970083

Cited by 3 publications

(2 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Three-dimensional visualizations of the thyroid are also crucial for surgical intervention [39]. Recent advances in segmentation and image processing techniques have enabled 3D thyroid reconstruction from 2D ultrasound slices [40,41].…”

Section: Discussionmentioning

confidence: 99%

Imaging the Human Thyroid Using Three-Dimensional Diffuse Optical Tomography: A Preliminary Study

et al. 2021

View full text Add to dashboard Cite

Thyroid cancer is usually diagnosed by ultrasound imaging and fine-needle aspiration biopsy. However, diagnosis of follicular thyroid carcinomas (FTC) is difficult because FTC lacks nuclear atypia and a consensus on histological interpretation. Diffuse optical tomography (DOT) offers the potential to diagnose FTC because it can measure tumor hypoxia, while image reconstruction of the thyroid is still challenging mainly due to the complex anatomical features of the neck. In this study, we attempted to solve this issue by creating a finite element model of the human neck excluding the trachea (a void region). By reconstruction of the absorption coefficients at three wavelengths, 3D tissue oxygen saturation maps of the human thyroid are obtained for the first time by DOT.

show abstract

Section: Discussionmentioning

confidence: 99%

Imaging the Human Thyroid Using Three-Dimensional Diffuse Optical Tomography: A Preliminary Study

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Poudel (2016) et al [9] segmented thyroid images in 703 images and passed them to a 3D reconstruction algorithm to obtain a 3D model of the thyroid. Ciora (2019) et al [10] achieved a technique for the thyroid 3D model reconstruction from 2D images provided by an ultrasound system using image processing and pattern recognition. Wein (2020) et al [11] proposed a framework for deep learning-based trajectory estimation of overlapping horizontal and sagittal image data to assist in 3D model optimization.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional Visualization of Thyroid Ultrasound Images Based on Multi-scale Features Fusion and Hierarchical Attention

Mi,

Wang,

Feng

et al. 2023

Preprint

View full text Add to dashboard Cite

Background The incidence of thyroid disorders is increasing every year. Three-dimensional visualization of the thyroid gland and its surrounding tissues based on free-arm ultrasound scanning videos is essential for identifying the thyroid and related tissues in the neck and screening for associated diseases. However, the key to achieving 3D visualization lies in the multi-target segmentation of neck tissues. Currently, the accuracy of multi-target segmentation for thyroid ultrasound images are unsatisfactory. Method Therefore, in order to enhance the multi-target segmentation accuracy for the thyroid and its surrounding tissues and improve the 3D visualization, in this paper we proposed PA-Unet++. Pyramid pooling module helps in the segmentation of multi-organization with different sizes by integrating multi-scale feature information. Additionally, attention gating mechanism is applied to each decoding layer to progressively highlight the target tissue and suppress the representation of background pixels. Results With 4600 images containing 23,000 annotated regions are divided into training and test sets at a ratio of 9:1, the results show that: compared with the results of U-net++, the Dice of our model increased from 78.78–81.88% (+ 3.10%), the mIOU increased from 73.44–80.35% (+ 6.91%), the PA index increased from 92.95–94.79% (+ 1.84%). Conclusions This indicates that PA-Unet + + has a higher accuracy for segmentation of multiple tissues in thyroid ultrasound images. The segmentation results can optimize the 3D visualization.

show abstract

Three-dimensional visualization of thyroid ultrasound images based on multi-scale features fusion and hierarchical attention

Mi,

Wang,

Feng

et al. 2024

BioMed Eng OnLine

View full text Add to dashboard Cite

Background Ultrasound three-dimensional visualization, a cutting-edge technology in medical imaging, enhances diagnostic accuracy by providing a more comprehensive and readable portrayal of anatomical structures compared to traditional two-dimensional ultrasound. Crucial to this visualization is the segmentation of multiple targets. However, challenges like noise interference, inaccurate boundaries, and difficulties in segmenting small structures exist in the multi-target segmentation of ultrasound images. This study, using neck ultrasound images, concentrates on researching multi-target segmentation methods for the thyroid and surrounding tissues. Method We improved the Unet++ to propose PA-Unet++ to enhance the multi-target segmentation accuracy of the thyroid and its surrounding tissues by addressing ultrasound noise interference. This involves integrating multi-scale feature information using a pyramid pooling module to facilitate segmentation of structures of various sizes. Additionally, an attention gate mechanism is applied to each decoding layer to progressively highlight target tissues and suppress the impact of background pixels. Results Video data obtained from 2D ultrasound thyroid serial scans served as the dataset for this paper.4600 images containing 23,000 annotated regions were divided into training and test sets at a ratio of 9:1, the results showed that: compared with the results of U-net++, the Dice of our model increased from 78.78% to 81.88% (+ 3.10%), the mIOU increased from 73.44% to 80.35% (+ 6.91%), and the PA index increased from 92.95% to 94.79% (+ 1.84%). Conclusions Accurate segmentation is fundamental for various clinical applications, including disease diagnosis, treatment planning, and monitoring. This study will have a positive impact on the improvement of 3D visualization capabilities and clinical decision-making and research in the context of ultrasound image.

show abstract

A Simple Method for 3D Thyroid Reconstruction from 2D Ultrasound Slices

Cited by 3 publications

References 3 publications

Imaging the Human Thyroid Using Three-Dimensional Diffuse Optical Tomography: A Preliminary Study

Imaging the Human Thyroid Using Three-Dimensional Diffuse Optical Tomography: A Preliminary Study

Three-dimensional Visualization of Thyroid Ultrasound Images Based on Multi-scale Features Fusion and Hierarchical Attention

Three-dimensional visualization of thyroid ultrasound images based on multi-scale features fusion and hierarchical attention

Contact Info

Product

Resources

About