A system for mapping anatomical tissue, comprising: a device having a shaft, a housing attached to a distal portion of the shaft, and at least one ultrasound transducer disposed in the housing, wherein the at least one ultrasound transducer is configured to provide signal data corresponding to detected tissue in proximity to the at least one ultrasound transducer, wherein the shaft further comprises a channel through the shaft from the distal portion to a proximal portion, wherein the channel is configured to allow passage of a surgical tool through the shaft there through; and a computing device configured to: identify an anatomical structure by analyzing the signal data by execution of a classification algorithm, wherein the classification algorithm identifies the anatomical structure by comparing a b-mode scan line from the signal data to a plurality of known b-mode scan lines, each known b-mode scan line having been associated with a corresponding type of anatomical structure; and generate, for display, a 2-D mapping or a 3-D volumetric image depicting the anatomical structure, wherein by being configured to identify the anatomical structure by analyzing the signal data by execution of the classification algorithm, the computing device is configured to: threshold a b-mode image of the signal data to generate a binary map of intensity values; after thresholding the b-mode image, filter the b-mode image with a smoothing filter; identify contiguous regions in the filtered b-mode image having a pixel count above a minimum threshold and below a maximum threshold; compare the identified contiguous regions to an area of an ellipse outlining the contiguous regions; and classify the identified contiguous regions as a nerve based on the comparison. a device having a shaft, a housing attached to a distal portion of the shaft, and at least one ultrasound transducer disposed in the housing, wherein the at least one ultrasound transducer is configured to provide signal data corresponding to detected tissue in proximity to the at least one ultrasound transducer, wherein the shaft further comprises a channel through the shaft from the distal portion to a proximal portion, wherein the channel is configured to allow passage of a surgical tool through the shaft there through; and a computing device configured to: identify an anatomical structure by analyzing the signal data by execution of a classification algorithm, wherein the classification algorithm identifies the anatomical structure by comparing a b-mode scan line from the signal data to a plurality of known b-mode scan lines, each known b-mode scan line having been associated with a corresponding type of anatomical structure; and generate, for display, a 2-D mapping or a 3-D volumetric image depicting the anatomical structure, wherein by being configured to identify the anatomical structure by analyzing the signal data by execution of the classification algorithm, the computing device is configured to: threshold a b-mode image of the signal data to generate a binary map of intensity values; after thresholding the b-mode image, filter the b-mode image with a smoothing filter; identify contiguous regions in the filtered b-mode image having a pixel count above a minimum threshold and below a maximum threshold; compare the identified contiguous regions to an area of an ellipse outlining the contiguous regions; and classify the identified contiguous regions as a nerve based on the comparison. identify an anatomical structure by analyzing the signal data by execution of a classification algorithm, wherein the classification algorithm identifies the anatomical structure by comparing a b-mode scan line from the signal data to a plurality of known b-mode scan lines, each known b-mode scan line having been associated with a corresponding type of anatomical structure; and generate, for display, a 2-D mapping or a 3-D volumetric image depicting the anatomical structure, wherein by being configured to identify the anatomical structure by analyzing the signal data by execution of the classification algorithm, the computing device is configured to: threshold a b-mode image of the signal data to generate a binary map of intensity values; after thresholding the b-mode image, filter the b-mode image with a smoothing filter; identify contiguous regions in the filtered b-mode image having a pixel count above a minimum threshold and below a maximum threshold; compare the identified contiguous regions to an area of an ellipse outlining the contiguous regions; and classify the identified contiguous regions as a nerve based on the comparison. threshold a b-mode image of the signal data to generate a binary map of intensity values; after thresholding the b-mode image, filter the b-mode image with a smoothing filter; identify contiguous regions in the filtered b-mode image having a pixel count above a minimum threshold and below a maximum threshold; compare the identified contiguous regions to an area of an ellipse outlining the contiguous regions; and classify the identified contiguous regions as a nerve based on the comparison.