We present a new algorithm, called marching cubes, that creates triangle models of constant density surfaces from 3D medical data. Using a divide-and-conquer approach to generate inter-slice connectivity, we create a case table that defines triangle topology. The algorithm processes the 3D medical data in scan-line order and calculates triangle vertices using linear interpolation. We find the gradient of the original data, normalize it, and use it as a basis for shading the models. The detail in images produced from the generated surface models is the result of maintaining the inter-slice connectivity, surface data, and gradient information present in the original 3D data. Results from computed tomography (CT), magnetic resonance (MR), and single-photon emission computed tomography (SPECT) illustrate the quality and functionality of marching cubes. We also discuss improvements that decrease processing time and add solid modeling capabilities.

/pdf/marching-cubes-a-high-resolution-3d-surface-construction-3ealswkmtb.pdf

Marching cubes: A high resolution 3D surface construction algorithm

Ultrasound is an inexpensive and widely used imaging modality for the diagnosis and staging of a number of diseases. In the past two decades, it has benefited from major advances in technology and has become an indispensable imaging modality, due to its flexibility and non-invasive character. In the last decade, research investigators and commercial companies have further advanced ultrasound imaging with the development of 3D ultrasound. This new imaging approach is rapidly achieving widespread use with numerous applications. The major reason for the increase in the use of 3D ultrasound is related to the limitations of 2D viewing of 3D anatomy, using conventional ultrasound. This occurs because: (a) Conventional ultrasound images are 2D, yet the anatomy is 3D, hence the diagnostician must integrate multiple images in his mind. This practice is inefficient, and may lead to variability and incorrect diagnoses. (b) The 2D ultrasound image represents a thin plane at some arbitrary angle in the body. It is difficult to localize the image plane and reproduce it at a later time for follow-up studies. In this review article we describe how 3D ultrasound imaging overcomes these limitations. Specifically, we describe the developments of a number of 3D ultrasound imaging systems using mechanical, free-hand and 2D array scanning techniques. Reconstruction and viewing methods of the 3D images are described with specific examples. Since 3D ultrasound is used to quantify the volume of organs and pathology, the sources of errors in the reconstruction techniques as well as formulae relating design specification to geometric errors are provided. Finally, methods to measure organ volume from the 3D ultrasound images and sources of errors are described.

https://iopscience.iop.org/article/10.1088/0031-9155/46/5/201/pdf

Three-Dimensional Ultrasound Imaging

Three-dimensional (3D) medical images of computed tomographic (CT) data sets can be generated with a variety of computer algorithms. The three most commonly used techniques are shaded surface display, maximum intensity projection, and, more recently, 3D volume rendering. Implementation of 3D volume rendering involves volume data management, which relates to operations including acquisition, resampling, and editing of the data set; rendering parameters including window width and level, opacity, brightness, and percentage classification; and image display, which comprises techniques such as "fly-through" and "fly-around," multiple-view display, obscured structure and shading depth cues, and kinetic and stereo depth cues. An understanding of both the theory and method of 3D volume rendering is essential for accurate evaluation of the resulting images. Three-dimensional volume rendering is useful in a wide variety of applications but is just now being incorporated into commercially available software packages for medical imaging. Although further research is needed to determine the efficacy of 3D volume rendering in clinical applications, with wider availability and improved cost-to-performance ratios in computing, 3D volume rendering is likely to enjoy widespread acceptance in the medical community.

Three-dimensional Volume Rendering of Spiral CT Data: Theory and Method

The development of 3-D ultrasound imaging is a way to address the disadvantages of conventional ultrasound imaging. In this article the authors review approaches that have been attempted in the development of 3-D ultrasound imaging such as 3-D B-mode, color Doppler, and power Doppler systems. Acquisition, reconstruction, and rendering techniques for 3-D imaging are discussed, as well as applications and limitations.

3-D ultrasound imaging: a review

http://www.pages.drexel.edu/~sunwei/WSUN-Papers/J-CMPB-CATE.pdf

Recent development on computer aided tissue engineering--a review.

Three dimensional reconstruction images of bony and soft tissue surfaces have improved understanding of complex facial deformities. Applied to CT studies of complex craniofacial abnormalities, this method has delineated abnormal facial soft tissue and bony morphology, facilitated surgical planning, and improved quantitative postoperative evaluation. Advanced computer-aided aircraft design techniques were adapted and applied to craniofacial surgical procedure-planning and evaluation using surface contours obtained from CT scans.

J O Warren

Papers

Three dimensional CT reconstruction images for craniofacial surgical planning and evaluation.

Computerized imaging for soft tissue and osseous reconstruction in the head and neck.