The base-emitter shorted configuration exhibits a flatter JC versus V curve when in reverse bias compared with the base-collector configuration. The two configurations are implemented using the austriamicrosystems AG 0.35-μm process. The parameters measured are current density-voltage, capacitance-voltage, and noise. The two configurations that are considered differ the first is a base-emitter shorted HBT and the second is a base-collector shorted HBT. Characterization is done to understand the behavior of these diodes for near-infrared detecting applications at room temperature and 77 K. The characterization of SiGe diode-connected heterojunction bipolar transistors (HBTs) through measurements of two-circuit configurations is presented. However, we need further extensive studies to verify the proposed method for various CT scan conditions with many more patient images. We observed that the proposed method outperforms the original DSC method when metal artifacts were severe. We have applied the proposed method to the phantom and patient images taken at the X-ray tube voltage of 90 kVp. In the sinogram correction with the DSC mapping function, we apply the weighting proportional to the metal path length. We first segment the metallic objects in the CT image, and then we forward-project the segmented metal mask to identify the metal traces in the projection data with computing the metal path length for the rays penetrating the metal mask. We propose a modified DSC method to reduce severe metal artifacts, and we have tested it on human dental images. The direct sinogram correction (DSC) method, which directly corrects the sinogram using the mapping function derived by minimizing the sinogram inconsistency, works well in the case of mild metal artifacts, but it often fails to correct severe metal artifacts. Since lower tube voltages are used for dental CTs in spite of the more frequent presence of metallic objects in the patient, metal artifacts appear more severely in dental CT images, and the artifacts often persist even after metal artifact correction. Metal artifacts in dental computed tomography (CT) images, caused by highly X-ray absorbing objects, such as dental implants or crowns, often more severely compromise image readability than in medical CT images.
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