Abstract: A system includes a training server that in a training phase causes a custom neural network model for foliage detection to learn features related to foliage from a modified training dataset and further learn a color variation range of a predefined color associated with the features. A combination of the features related to foliage and the color variation range of the predefined color is utilized to obtain a trained custom neural network model that is deployed in a camera apparatus. The camera apparatus in the operational phase captures a new color image of an agricultural field, operates the trained custom neural network model to detect one or more foliage regions in the new color image in a real time or near real time, and operates at least one of a plurality of agricultural implements, based on the detected one or more foliage regions in the new color image.

Abstract: A camera apparatus including a central processing unit configured to capture raw image sensor data of a field-of-view of an agricultural field, concurrently execute a plurality of different image transformation operations in a single pass on the captured raw image sensor data to obtain a processed image output, based on an one-time read of pixel values of the captured raw image sensor data and push the processed image output in a shared memory accessible to a plurality of application nodes in the camera apparatus. The camera apparatus includes a graphical processing unit configured to cause the plurality of application nodes to concurrently access the processed image output from the shared memory to detect one or more foliage regions or one or more crop plants in the processed image output.

Abstract: A camera apparatus acquires an input color image of an agricultural field and generates a first binary mask image from the input color image. The first binary mask image includes one or more foliage masks indicative of a presence of one or more foliage regions in a field-of-view with a first accuracy level. One or more morphology operations are applied to remove noise in the first binary mask image and one or more image regions that meet a defined criteria to be considered as foliage are identified. An output binary mask image of foliage mask is generated, which is set as a ground truth to train a custom neural network model in a training phase. The trained custom neural network model is operated to detect one or more other foliage regions in a new color image captured by the camera apparatus in a real time or near real time.

Abstract: A camera apparatus includes control circuitry, where in a training phase, the control circuitry is configured to generate a set of binary images of foliage masks, where each binary image comprises one or more foliage regions demarcated from a non-foliage region. A modified training dataset of color images is generated and a custom neural network model for foliage detection is trained. The control circuitry causes the custom neural network model to not only learn a plurality of features related to foliage but also learn a color variation range of predefined color associated with the plurality of features and utilize combination of the plurality of features related to foliage and the color variation range to obtain trained custom neural network model. The control circuitry is configured to operate the trained custom neural network model to detect one or more foliage regions in a new color image in real time.

Abstract: A camera apparatus including a central processing unit configured to capture raw image sensor data of a field-of-view of an agricultural field, concurrently execute a plurality of different image transformation operations in a single pass on the captured raw image sensor data to obtain a processed image output, based on an one-time read of pixel values of the captured raw image sensor data and push the processed image output in a shared memory accessible to a plurality of application nodes in the camera apparatus. The camera apparatus includes a graphical processing unit configured to execute a first neural network model on the processed image output to detect one or more foliage regions in the processed image output and concomitantly execute a second neural network model on the processed image output to detect one or more crop plants in the processed image output.

Abstract: A camera apparatus includes control circuitry configured to acquire an input color image of an agricultural field, smoothen the input color image with a median blur and convert the smoothened input color image into a plurality of different color spaces. The control circuitry is configured to execute a set of channel operations on an individual channel or combined channels in each color space of the plurality of different color spaces and generate a normalized image based on outputs received from each color space processing path. The control circuitry is configured to determine a threshold value based on a histogram of the normalized image and apply the determined threshold value to generate a first binary mask image. The control circuitry is configured to apply one or more morphology operations to remove noise in the first binary mask image and generate an output binary mask image of foliage mask.

Abstract: A system mounted in a vehicle for agricultural applications includes a master apparatus and one or more slave apparatus. The master apparatus includes a central image-capture device and a master control device that is configured to acquire first geospatial location data including a first precision value and obtain location correction data from an external device. The master control device further generates a second geospatial location data including a second precision value by applying the location correction data to the first geospatial location data. The master control device further communicates the generated second geospatial location data to the slave control device. Thereafter, each slave control device is configured to determine one or more time slots in advance to automatically perform a determined action when the vehicle is in motion.

Abstract: A system mounted in a vehicle includes a plurality of image-capture devices to capture a sequence of color images corresponding to a plurality of field—of views (FOVs) of a plurality of defined areas. The system includes one or more hardware processors to determine a health state of a crop plant and a growth state of the crop plant. A spray mode is determined and dynamically selected from a predefined list of spray modes based on the determined health state of the crop plant, the growth state of the crop plant, and a type of chemical to be sprayed from the obtained sequence of colour images. A different set of electronically controlled sprayer nozzles is automatically operated at different time instants to release the selected type of chemical from a predefined number of the electronically controlled sprayer nozzles based on the selected spray mode.

Abstract: A modular apparatus mounted in a vehicle that includes an image-capture device that further includes a printed circuit board (PCB) having a perforation to accommodate an image-sensor and a plurality of layers of strobe-lights to surround the image-sensor. The modular apparatus includes a control device to control the image-capture device and determine a plurality of time instants at which the image-sensor and the plurality of layers of strobe-lights are activated. Furthermore, the control device captures a sequence of images of a field-of-view (FOV) of a defined area of a field at the determined plurality of time instants. Thereafter, the control device detects and tracks a crop plant in the defined area and generate a bounding box around the crop plant that is tracked. Further, the control device detects a plurality of buffer values and cause an implement to perform a predefined action on the crop plant.

Abstract: A system mounted in a vehicle includes a boom arrangement including a predefined number of electronically controllable sprayer nozzles and a plurality of image-capture devices. One or more hardware processors of the system are configured to obtain a plurality of images from the plurality of image-capture devices and receive geospatial location correction data from an external device. The one or more hardware processors are configured to execute mapping of pixel data of weeds or a crop plant in an image to distance information and cause a specific set of electronically controllable sprayer nozzles from amongst the predefined number of electronically controllable sprayer nozzles to operate based on a defined confidence threshold.

Abstract: Certain examples describe systems and methods for increasing plasma extracted from donor blood. An example method includes receiving blood extracted from a donor connected to a blood collection machine. The example method includes filtering the blood using a filtration device to remove at least a portion of plasma included in the blood to separate the plasma removed from remaining blood. The example method includes routing the plasma removed for collection. The example method includes re-filtering the remaining blood using a or the filtration device to remove additional plasma from the remaining blood. The example method includes routing the additional plasma removed for collection.

Abstract: Certain examples describe systems and methods for increasing plasma extracted from donor blood. An example method includes receiving blood extracted from a donor connected to a blood collection machine. The example method includes filtering the blood using a filtration device to remove at least a portion of plasma included in the blood to separate the plasma removed from remaining blood. The example method includes routing the plasma removed for collection. The example method includes re-filtering the remaining blood using a or the filtration device to remove additional plasma from the remaining blood. The example method includes routing the additional plasma removed for collection.

Abstract: Certain examples describe systems and methods for increasing plasma extracted from donor blood. An example method includes receiving blood extracted from a donor connected to a blood collection machine. The example method includes filtering the blood using a filtration device to remove at least a portion of plasma included in the blood to separate the plasma removed from remaining blood. The example method includes routing the plasma removed for collection. The example method includes re-filtering the remaining blood using a or the filtration device to remove additional plasma from the remaining blood. The example method includes routing the additional plasma removed for collection.

Abstract: Certain examples describe systems and methods for increasing plasma extracted from donor blood. An example method includes receiving blood extracted from a donor connected to a blood collection machine. The example method includes filtering the blood using a filtration device to remove at least a portion of plasma included in the blood to separate the plasma removed from remaining blood. The example method includes routing the plasma removed for collection. The example method includes re-filtering the remaining blood using a or the filtration device to remove additional plasma from the remaining blood. The example method includes routing the additional plasma removed for collection.

Abstract: A method for operating a medical imaging system is provided. The method includes receiving an image data set of a region of interest in a first dimensional representation, reducing the dimensionality of the image data set to a second dimensional representation, selecting a feature of interest in the second dimensional representation, and generating an image of the selected feature in the first dimensional representation.

Abstract: System and method for ganged ultrasound scanners is described. The described system includes a plurality of ultrasound scanners configured as a network and at least one connector for connecting a single ultrasound probe to the plurality of ultrasound scanners. The connector is configured to provide communication between the plurality of ultrasound scanners and the ultrasound probe.

Abstract: Certain embodiments include a system and method for an improved image acquisition rate in an ultrasound imaging system. The system includes an encoder for encoding an ultrasound signal with a code for transmission to form an encoded ultrasound signal, a transmitter for transmitting the encoded ultrasound signal, and a receiver for receiving an encoded echo signal produced based on the encoded ultrasound signal, wherein the receiver decodes the encoded echo signal to produce a decoded echo signal. The transmitter may include a transducer array for transmitting the encoded ultrasound signal. The receiver may include a separate transducer element or a dedicated transducer element of the transmitter transducer array. The system further includes a processor for determining a position of a scatterer based on a time of transmission of the encoded ultrasound signal, a time of reception of the encoded echo signal, and a strength of the encoded echo signal.

Abstract: A technique is provided for obfuscating or masking indicia viewable in a reconstructed image. Image data is acquired and stored and then accessed and the reconstructed image is analyzed to determine whether any indicia are viewable in the image that are in need of masking. Such indicia may include, for example, patient-identifying data. Other information may be left unmasked, such as orientation information, descriptive information, dates, and so forth. The technique permits automated recognition of indicia and altering of image data files so as to render certain sensitive information undecipherable in the processed reconstructed images.

Abstract: A medical imaging system including a central processing unit, a data storage unit in communication with said central processing unit, an imaging device in electrical communication with the central processing unit, and a biometric authorization unit in electrical communication with the central processing unit. A user inputs a biometric identifier into the biometric authorization unit in order to enable the medical imaging system.

Abstract: A system and method to identify a patient for imaging and information systems in a health care enterprise. A health care enterprise has a facility which includes typically equipment and the user. The system comprises the means for assigning a patient identifier-domain (PIDD) to a patient registration service in the health care enterprise. A means for assigning a default patient-identifier-domain (Default PIDD) to each facility, equipment and user. A means for assigning a patient-identifier (PID) to the patient. A means for assigning a global patient-identifier-domain identification (PIDD-ID) to each PIDD. A means for associating each PIDD with the PIDD-ID. And a means for associating the PID with the PIDD to create a unique patient identifier.