【视频摘要】Rapid and high-quality 3D fusion of heterogeneous CT...

Original KouShare 蔻享学术 2021-04-25

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Data obtained from computed tomography (CT) and magnetic resonance imaging (MRI) that describe the human brain is commonly used in medical research and diagnosis [1]. CT data are used to efficiently present high-density features, whereas MRI data are better suited for soft-tissue presentation [2]. The complementary functions of CT and MRI may be used to further develop medical care procedures and brain exploration. CT and MRI were combined to realistically depict the diagnostic, anatomic, and pathological information of the auditory and vestibular systems [3]. For brain tumor surgery, medical professionals often prefer to simultaneously visualize high-density structures (e.g., the skull structure) using CT and soft-tissue structures (e.g., the size and shape of tumors) using MRI to successfully determine the best craniotomy position [2].
Related work. The technique of volume rendering includes three stages: data preprocessing, lighting model construction, and image generation.
The fusion accomplished in the data preprocessing stage is accurate but complicated because multiple types of data obtained from a single sampling point are merged, including the density values and computable gradients. Mutual information was used to obtain three-dimensional (3D) fusion information, which was then integrated into a common framework using extensive computation [4]. Based on the developed method, a fully automatic scheme for multimodal heterogeneous data visual ization was successfully designed [5].
Fusion in light accumulation comprises two methods: fusion of the color and opacity of different heterogeneous data, followed by accumulation, and separate accumulation of heterogeneous data, followed by fusion. Liao et al. [6] proposed a 3D fusion algorithm for positron emission tomography (PET) and CT with a grayscale difference.
The simplest and most intuitive form of fusion is performed in the image-generation stage. Fusion is commonly achieved via color blending; however, traditional layered blending performed using color blending with transparency has certain limitations [7]; it can at most display only four layers. To ensure an accurate visual representation, Kuhne et al. [8] proposed a color perception method that blends two colors when the color tone changes.
Methods. (1) Visualization of CT volume data. For the visualization of the CT volume data of the brain, tissues are usually divided into three layers: skin, muscle, and bone [9]. To minimize the overlap between two adjacent substances, the used transfer function can be described as a multiple trapezoid, each representing one of the tissue layers.
(2) Visualization of MRI volume data. The visualization of MRI data is more complicated than that of CT data; we describe its main processing stages as follows.

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