One or more devices, systems, methods and storage mediums for performing medical procedure (e.g., needle guidance, ablation, biopsy, etc.) planning and/or performance, and/or for performing registration using at least one mask, are provided. Examples of applications for such devices, systems, methods and storage mediums include imaging, evaluating and diagnosing biological objects, such as, but not limited to, lesions and tumors, and such devices, systems, methods and storage mediums may be used for radiotherapy applications (e.g., to determine whether to place seed(s) for radiotherapy). The devices, systems, methods and storage mediums provide improved registration results by utilizing at least one mask to suppress one or more artifacts or objects (which may or may not include, but is not limited to, at least one medical instrument or tool) in an image including a portion of the medical guidance device and/or to enhance a region or target of interest in the image.

One or more devices, systems, methods and storage mediums for performing medical procedure (e.g., needle guidance, ablation, biopsy, etc.) planning and/or performance, and/or for performing registration using at least one mask, are provided. Examples of applications for such devices, systems, methods and storage mediums include imaging, evaluating and diagnosing biological objects, such as, but not limited to, lesions and tumors, and such devices, systems, methods and storage mediums may be used for radiotherapy applications (e.g., to determine whether to place seed(s) for radiotherapy). The devices, systems, methods and storage mediums provide improved registration results by utilizing at least one mask to suppress one or more artifacts or objects (which may or may not include, but is not limited to, at least one medical instrument or tool) in an image including a portion of the medical guidance device and/or to enhance a region or target of interest in the image.

Methods and apparatuses for performing a nanoarray-in-microarray assay is provided, which can be used to estimate a protein concentration in a sample solution. A plurality of nanodots are fabricated on a surface having at least one affinity binder. One or more microspots are superimposed over the nanodots on predetermined regions of the surface, each of the microspots comprising at least one antibody. An assay process is performed on the surface, and the surface is imaged to acquire optical images of the nanodots within each microspot. Image analysis algorithms are the performed on the optical images to identify bindings on individual ones of the plurality of nanodots.

Techniques are provided for enhancement of edges in image frames using depth information. A methodology implementing the techniques according to an embodiment includes receiving a color image frame and a depth map frame. The method also includes generating a sharpness mask to control the application of image sharpening to the color pixels. The sharpness mask is based on the value of depth pixels corresponding to the color pixels; and on properties of the depth camera that generated the color image frame, including depth of field, focal distance, and hyperfocal distance. The method further includes calculating sharpness strength for the color pixels. The sharpness strength is proportional to the value of the depth pixel corresponding to the color pixel. The method further includes applying a sharpening filter to the color image frame to enhance edge image features. The sharpening filter is based on the sharpness mask and the sharpness strength.

An image processing apparatus includes a first acquisition unit configured to acquire noise information about a noise characteristic of an input image generated by image capturing using an optical system, a second acquisition unit configured to acquire a sharpening filter in a real space, the sharpening filter being based on an optical characteristic of the optical system, and a third acquisition unit configured to acquire gain information about gain of the sharpening filter using components of the sharpening filter. The image processing apparatus performs sharpening processing on the input image based on the noise information and the gain information.

An imaging device includes: an optical system which obtains an optical image of a photographic subject; an image sensor which converts the optical image to an electric signal; a digital signal processor which produces image data based on the electric signal; a display section which displays a photographic subject image expressed by the image data; and an operating section which performs a necessary setting regarding imaging, the digital signal processor including: an autofocus operation section which performs an autofocus operation based on data of an autofocus area set in the photographic subject image; a main area setting section which sets a main area in the photographic subject image; and a blurring operation section which performs a blurring operation on an area other than the main area in the photographic subject image, wherein the autofocus area is set automatically to overlap with at least a part of the main area.

Systems and methods of enhancing the resolution of digital terrain models (DTM) for location-based applications and analyses. The DTM enhancement process takes the signature of the input image (e.g., via the input image and a noise surface file with similar characteristics as the sensor used to capture the input image) and applies it to the DTM without including large features such as buildings. The disclosed methods include utilize a process similar to that used for enhancing a DSM based on mapping the changing intensity from the image file to changes in elevation in the DSM using a regression over a local neighborhood of pixels. Further, the disclosed methods do not rely on information about the sensors and are extendable to be able to utilize any types of images. Additionally, the disclosed embodiments are sensor agnostic and can be applied on any type of image collected by any type of sensor.

One embodiment provides a method, including: receiving a plurality of communication events associated with a pixel of an imaging device; identifying a frequency associated with the communication events, wherein the identifying a frequency comprises determining a number of communication events occurring within a predetermined time interval or determining a time interval between the communication events; determining, from the identified frequency, whether the pixel comprises a non-conforming pixel; and masking, if the pixel comprises a non-conforming pixel, subsequent communication events from the non-conforming pixel. Other aspects are described and claimed.

One embodiment provides a method, including: receiving a plurality of communication events associated with a pixel of an imaging device; identifying a frequency associated with the communication events, wherein the identifying a frequency comprises determining a number of communication events occurring within a predetermined time interval or determining a time interval between the communication events; determining, from the identified frequency, whether the pixel comprises a non-conforming pixel; and masking, if the pixel comprises a non-conforming pixel, subsequent communication events from the non-conforming pixel. Other aspects are described and claimed.

In one embodiment, a system may access an image of a face and generate blurred color information and blurred brightness information based on the image's color information. The system may detect edge information associated with the face based on the blurred brightness information. The edge information may identify regions in the image that correspond to edges of the face. The system may modify the blurred color information based on the edge information associated with the face. Edge color information may be determined based on the modified blurred color information and the image. The system may generate smoothed color information based on the color information of the image and modify the smoothed color information based on the edge color information. The system may generate an output of the face with smoothed skin using a portion of the color information of the image and a portion of the modified smoothed color information.