Ultrasound Visualization using VTK

This paper [3] discusses the utilization of PACS in medical imaging and how it stores and retrieves DICOM information using RDBMS. The benefits of using PACS, such as research, treatment strategies, and disease progression monitoring, are also highlighted. Additionally, the paper introduces 3D techniques in medical imaging, including MPR, SR, and VR, and discusses how they can be used to visualize tumors and other objects. Image segmentation is also discussed as a method of breaking down digital images into subgroups for analysis. Overall, the paper provides an overview of how PACS and 3D imaging techniques can benefit medical professionals in treating patients.

The paper[4] proposes an algorithm for 3D reconstruction of brain tumors from MRI images involves segmentation, Delaunay triangulation, and triangular surface visualization. Pre-processing and segmentation involve noise elimination, histogram equalization, and elimination of the skull region. Mathematical morphology is used for image processing. The algorithm calculates the contour plot of the matrix Z using vectors x and y to control scaling on the x and y-axes, and the contours are superimposed in 3D to create a better 3D reconstruction of the brain tumor from MRI images. The algorithm shows promising results for tumor detection and could be used for diagnostic purposes.

In this project, two different filters, median and Gaussian, were used to perform data preprocessing on ultrasound images. The median filter was applied to remove the noise from the ultrasound data, while the Gaussian filter was used to blur the images and reduce noise. The filters were applied using the Visualization Toolkit library, and the resulting preprocessed ultrasound data was saved in the Meta Image Format. The Gaussian filter performed well in reducing Gaussian noise and high-frequency noise, such as speckle noise, which is common in ultrasound images.

Data preprocessing using median and Gaussian filters was crucial in this project to improve the quality of the ultrasound images and enhance the accuracy of the subsequent visualization algorithms. By removing noise and smoothing out the image, the filters provided clearer and more accurate ultrasound data for visualization. The use of standard file formats such as MHA ensured that the preprocessed ultrasound data was easily accessible and compatible with other medical imaging software. Overall, data preprocessing was a vital step in the ultrasound visualization process and helped to ensure the accuracy and reliability of the final visualization results.

One of the main visualization techniques used in the project for ultrasound data was isosurface extraction, which involves generating a 3D surface from a 3D image dataset by selecting a threshold value and extracting all the voxels with a value above that threshold [6]. This technique was applied in conjunction with a Gaussian filter to enhance the image quality of the ultrasound data, resulting in a clear and detailed 3D view of the ultrasound data. The web application developed for the project allows users to adjust the marching cubes threshold used in the isosurface extraction technique to fine-tune the visualization to their specific needs, giving them more flexibility when visualizing ultrasound data.

The combination of isosurface extraction and the Gaussian filter proved to be an effective technique in enhancing the image quality of the ultrasound data. Isosurface extraction allowed for the generation of a 3D surface that provided a more detailed and accurate representation of the ultrasound data. The Gaussian filter helped to reduce noise and improve the overall quality of the images, resulting in a clearer visualization. The ability to adjust the marching cubes threshold in real-time through the web application provides users with the flexibility to optimize the visualization according to their preferences and specific needs.

Delaunay triangulation 2D is another visualization technique used in the project to visualize ultrasound data [7]. It is used to generate a set of non-overlapping triangles from a set of points. The resulting triangulation maximizes the minimum angle of all the triangles, providing a smoother and more regular visualization. This technique was used in conjunction with a Gaussian filter to enhance the image quality of ultrasound data as shown in 3.

The web application developed for the project includes the ability to switch between Delaunay triangulation 2D and isosurface extraction techniques in real-time, enabling users to compare and choose the best technique for their specific needs. The application also includes an adjustable marching cubes threshold, which allows users to fine-tune the visualization. Overall, the resulting visualization provides a clear and detailed 2D view of the ultrasound data.

TThe Ultrasound Visualization Web Application was developed to provide medical practitioners with an accessible platform for displaying ultrasound data. The online application is easily accessible from any device with an internet connection, without the need for additional software installation. Medical practitioners can upload their own Meta Image Formatted dataset and view it using the visualization techniques available in real-time via the user-friendly interface. This gives medical practitioners more flexibility in visualizing ultrasound data, enabling them to concentrate on certain areas of interest or spot potential problems that conventional ultrasound visualization approaches may have overlooked.

The server-side application processes the MHA dataset uploaded by users to the website. The pre-processing of ultrasound data using a Gaussian filter increases the precision and reliability of the images. The data is then processed through the isosurface extraction and Delaunay triangulation algorithms, offering special anatomical insights. The web application presents a 3D representation of the ultrasound data after processing, which can be rotated and adjusted to highlight regions of interest. The user can switch between several visualization techniques, adjust the marching cubes threshold, and study the data in real-time to better understand the patient’s anatomy.

The usability study of the ultrasound visualisation web application showed positive results with high average ratings across all evaluated areas. Participants found the application easy to learn and use, and consistent in behaviour. While there is room for improvement in terms of efficiency, the app’s user-friendly design suggests its potential for increased popularity and utility in medical contexts. Further research could assess its effectiveness in specific medical situations for diagnosis and treatment planning.

The ultrasound visualization web application has received positive feedback from medical experts for its potential to improve the accuracy and reliability of ultrasound imaging. However, it’s important to use the visualization alongside other diagnostic tools and medical expertise, and to ensure the accuracy of the ultrasound data obtained through appropriate protocols and equipment. Switching between isosurface extraction and Delaunay triangulation can provide unique insights into the patient’s anatomy, highlighting surface features and offering a more detailed view of internal structures.