An apparatus for detecting a locating medium in tissue includes a probe, and a console. The probe includes a handle and a detector disposed on a distal end of the probe. The console is in communication and includes a display. The display has a first graphical representation and a second graphical representation. The first graphical representation is configured to depict a count real-time count based on a signal from the detector. The second graphical representation is configured to depict a target count.

An apparatus for detecting a locating medium in tissue includes a probe, and a console. The probe includes a handle and a detector disposed on a distal end of the probe. The console is in communication and includes a display. The display has a first graphical representation and a second graphical representation. The first graphical representation is configured to depict a count real-time count based on a signal from the detector. The second graphical representation is configured to depict a target count.

An instrument and software methodology to detect a radioactive source and incorporates the following:

1) two radiation detectors in a co-axial configuration, housed in a handheld probe, and

2) a gamma detection control unit executing software algorithms to limit the functional field of view to the front aspect of the probe, vary the depth and width of the field of view to provide collimation without the use of metallic shielding, and allowing the instrument to measure the distance to the radiation source.

An instrument and software methodology to detect a radioactive source and incorporates the following:

1) two radiation detectors in a co-axial configuration, housed in a handheld probe, and

2) a gamma detection control unit executing software algorithms to limit the functional field of view to the front aspect of the probe, vary the depth and width of the field of view to provide collimation without the use of metallic shielding, and allowing the instrument to measure the distance to the radiation source.

A planar-symmetry device for high-sensitivity gamma ray detection, which allows real-time tomography image reconstruction with very good spatial resolution. Advantageously, the multi-pinhole collimators of the device move during data collection and/or one or more of the pinholes thereof moves independently, thereby allowing possible artifacts resulting from overlap areas of the detector to be completely eliminated.

A planar-symmetry device for high-sensitivity gamma ray detection, which allows real-time tomography image reconstruction with very good spatial resolution. Advantageously, the multi-pinhole collimators of the device move during data collection and/or one or more of the pinholes thereof moves independently, thereby allowing possible artifacts resulting from overlap areas of the detector to be completely eliminated.

An apparatus and method to obtain input projection data based on radiation detected at a plurality of detector elements, reconstruct plural uncorrected images in response to applying a reconstruction algorithm to the input projection data, segment the plural uncorrected images into two or more types of material-component images by applying a deep learning segmentation network, generate output projection data corresponding to the two or more types of material-component images based on a forward projection, generate corrected multi material-decomposed projection data based on the generated output projection data corresponding to the two or more types of material-component images, and reconstruct the multi material-component images from the corrected multi material-decomposed projection data to generate one or more corrected images. In some embodiments, the plural uncorrected images are segmented into three or more types of material-component images by applying a deep learning segmentation network and beam hardening correction is performed for the three or more materials.

An apparatus and method to obtain input projection data based on radiation detected at a plurality of detector elements, reconstruct plural uncorrected images in response to applying a reconstruction algorithm to the input projection data, segment the plural uncorrected images into two or more types of material-component images by applying a deep learning segmentation network, generate output projection data corresponding to the two or more types of material-component images based on a forward projection, generate corrected multi material-decomposed projection data based on the generated output projection data corresponding to the two or more types of material-component images, and reconstruct the multi material-component images from the corrected multi material-decomposed projection data to generate one or more corrected images. In some embodiments, the plural uncorrected images are segmented into three or more types of material-component images by applying a deep learning segmentation network and beam hardening correction is performed for the three or more materials.

An anti-scatter collimator is for arrangement in a stacked construction with an X-ray detector. In an embodiment, the anti-scatter collimator includes collimator walls arranged adjacently at least along a first direction. The collimator walls are mutually spaced to provide a through-channel between each pair of adjacent collimator walls. The through-channels provided by the arrangement of the multiplicity of collimator walls are at least partially filled with a filler material.

An anti-scatter collimator is for arrangement in a stacked construction with an X-ray detector. In an embodiment, the anti-scatter collimator includes collimator walls arranged adjacently at least along a first direction. The collimator walls are mutually spaced to provide a through-channel between each pair of adjacent collimator walls. The through-channels provided by the arrangement of the multiplicity of collimator walls are at least partially filled with a filler material.