Abstract: The present disclosure provides a semiconductor device and a fabricating method thereof includes a source structure, a drain structure, a gate structure, a bottom dielectric layer, a gate dielectric layer, a channel structure, and a metal nitride layer. The source structure and the drain structure are stacked in a vertical direction, and the gate structure is between the drain structure and the source structure. The bottom dielectric layer is disposed between the drain structure and the source structure. The channel structure is disposed between the drain structure and the source structure and is electrically connected the drain structure and the source structure, and the channel structure is partially disposed in the gate structure. The gate dielectric layer is disposed between the channel structure and the gate structure. The metal nitride layer is disposed between the gate dielectric layer and the gate structure.

Abstract: A three-dimensional memory device includes a substrate and a stack structure including alternating conductive layers and dielectric layers disposed on the substrate, and a memory string structure extending vertically through the stack structure. The memory string structure includes a conductive pillar and a storage layer disposed between the conductive pillar and the stack structure and surrounding the conductive pillar. The storage layer includes a plurality of first protruding portions at interfaces between the conductive layers and the dielectric layers.

Abstract: A backing block for an ultrasonic transducer array stack of an ultrasound probe is formed as a composite structure of graphite foam impregnated with an epoxy resin. The epoxy resin penetrates the porous foam structure at least part-way into the depth of the graphite foam block and, when cured, provides the backing block with good structural stability. The composite graphite foam backing block is bonded to the integrated circuit of a transducer to provide high thermal conductivity away from the transducer and good acoustic attenuation or scattering of rearward acoustic reverberations.

Abstract: In one embodiment, a method of detecting centerline of a vessel is provided. The method comprises steps of acquiring a 3D image volume, initializing a centerline, initializing a Kalman filter, predicting a next center point using the Kalman filter, checking validity of the prediction made using the Kalman filter, performing template matching, updating the Kalman filter based on the template matching and repeating the steps of predicting, checking, performing and updating for a predetermined number of times. Methods of automatic vessel segmentation and temporal tracking of the segmented vessel is further described with reference to the method of detecting centerline.

Abstract: In one embodiment, a method of detecting centerline of a vessel is provided. The method comprises steps of acquiring a 3D image volume, initializing a centerline, initializing a Kalman filter, predicting a next center point using the Kalman filter, checking validity of the prediction made using the Kalman filter, performing template matching, updating the Kalman filter based on the template matching and repeating the steps of predicting, checking, performing, and updating for a predetermined number of times. Methods of automatic vessel segmentation and temporal tracking of the segmented vessel is further described with reference to the method of detecting centerline.

Abstract: A backing block for an ultrasonic transducer array stack of an ultrasound probe is formed as a composite structure of graphite foam impregnated with an epoxy resin. The epoxy resin penetrates the porous foam structure at least part-way into the depth of the graphite foam block and, when cured, provides the backing block with good structural stability. The composite graphite foam backing block is bonded to the integrated circuit of a transducer to provide high thermal conductivity away from the transducer and good acoustic attenuation or scattering of rearward acoustic reverberations.

Abstract: In one embodiment, a method of detecting centerline of a vessel is provided. The method comprises steps of acquiring a 3D image volume, initializing a centerline, initializing a Kalman filter, predicting a next center point using the Kalman filter, checking validity of the prediction made using the Kalman filter, performing template matching, updating the Kalman filter based on the template matching and repeating the steps of predicting, checking, performing, and updating for a predetermined number of times. Methods of automatic vessel segmentation and temporal tracking of the segmented vessel is further described with reference to the method of detecting centerline.

Abstract: In one embodiment, a method of detecting centerline of a vessel is provided. The method comprises steps of acquiring a 3D image volume, initializing a centerline, initializing a Kalman filter, predicting a next center point using the Kalman filter, checking validity of the prediction made using the Kalman filter, performing template matching, updating the Kalman filter based on the template matching and repeating the steps of predicting, checking, performing and updating for a predetermined number of times. Methods of automatic vessel segmentation and temporal tracking of the segmented vessel is further described with reference to the method of detecting centerline.

Abstract: In one embodiment, a method of detecting centerline of a vessel is provided. The method comprises steps of acquiring a 3D image volume, initializing a centerline, initializing a Kalman filter, predicting a next center point using the Kalman filter, checking validity of the prediction made using the Kalman filter, performing template matching, updating the Kalman filter based on the template matching and repeating the steps of predicting, checking, performing and updating for a predetermined number of times. Methods of automatic vessel segmentation and temporal tracking of the segmented vessel is further described with reference to the method of detecting centerline.

Abstract: In one embodiment, a method of detecting centerline of a vessel is provided. The method comprises steps of acquiring a 3D image volume, initializing a centerline, initializing a Kalman filter, predicting a next center point using the Kalman filter, checking validity of the prediction made using the Kalman filter, performing template matching, updating the Kalman filter based on the template matching and repeating the steps of predicting, checking, performing and updating for a predetermined number of times. Methods of automatic vessel segmentation and temporal tracking of the segmented vessel is further described with reference to the method of detecting centerline.