A calculation unit calculates a first error for a boundary region of an image represented by image data, calculates a second error for a non-boundary region different from the boundary region, and calculates an error between label data and an estimation result based on the first error and the second error. And an influence of the first error on the calculation by the calculation unit is controlled to be smaller than an influence of the second error on the calculation by the calculation unit.

A system for monitoring gluten consumption, especially in celiac people, which allows the feeding of food consumption data and updating, in real time, of the estimated amount of gluten consumed daily. Still, the present invention refers to a system for prediction that associates the possibility of an indisposition being associated or not with an undue consumption of gluten.

The present disclosure provides a system for predicting diabetic retinopathy progression. The system includes an image-capturing module and a processing unit. The image-capturing module is configured to capture a first fundus image of a user at a first time and a second fundus image of the user at a second time different from the first time. The processing unit is configured to receive the first fundus image and the second fundus image, compare the first fundus image and the second fundus image and indicate a difference between the first fundus image and the second fundus image. The processing unit is also configured to provide a prediction in a diabetic retinopathy progression of the user based on the difference. A method for predicting diabetic retinopathy progression is also provided in the present disclosure.

There is provided an image processing device including: a camera outputting a first image obtained by photographing an object that is moving; and a control module generating a coded pattern for controlling a shutter exposure time and reconstructing a second image in which motion blur of the first image is removed, wherein the control module detects a moving speed of the object, and generates the coded pattern based on a point spread function (PSF) range set according to the moving speed.

Provided herein are methods and systems for making patient-specific therapy recommendations of a combination of any two or more therapies selected from a lipid-lowering therapy, an anti-inflammatory therapy for patients with known or suspected cardiovascular disease, such as atherosclerosis.

The present invention relates to a device (2) and a method (100) for determining at least one final two-dimensional image or slice for visualizing an object of interest in a three-dimensional ultrasound volume. The method (100) for determining at least one final two-dimensional image, the method comprises the steps: a) providing (101) a three-dimensional image of a body region of a patient body, wherein an applicator configured for fixating at least one radiation source is inserted into the body region; b) providing (102) an initial direction, in particular by randomly determining the initial direction within the three-dimensional image; c) repeating (103) the following sequence of steps s1) to s4): s1) determining (104), via a processing unit, a set-direction within the three-dimensional image based on the initial direction for the first sequence or based on a probability map determined during a previous sequence; s2) extracting (105), via the processing unit, an image-set of two-dimensional images from the three-dimensional image, such that the two-dimensional images of the image-set are arranged coaxially and subsequently in the set-direction; s3) applying (106), via the processing unit, an applicator pre-trained classification method to each of the two-dimensional images of the image-set resulting in a probability score for each of the two-dimensional images of the image-set indicating a probability of the applicator being depicted, in particular fully depicted, in the respective two-dimensional image of the image-set in a cross-sectional view; and s4) determining (107), via the processing unit, a probability-map representing the probability scores of the two-dimensional images of the image-set with respect to the set-direction; wherein the method comprises the further step: d) determining (108), via a processing unit and after finishing the last sequence, the two-dimensional image associated with the highest probability score, in particular from the image-set determined during the last sequence, as the final two-dimensional image. The invention provides an efficient way to ensure that the ultrasound volume has the required clinical information by providing the necessary scan planes having the object of interest e.g. the applicator (6) in a three-dimensional ultrasound volume.

The present disclosure is directed to systems and methods for classifying biomedical images. A feature classifier may generate a plurality of tiles from a biomedical image. Each tile may correspond to a portion of the biomedical image. The feature classifier may select a subset of tiles from the plurality of tiles by applying an inference model. The subset of tiles may have highest scores. Each score may indicate a likelihood that the corresponding tile includes a feature indicative of the presence of the condition. The feature classifier may determine a classification result for the biomedical image by applying an aggregation model. The classification result may indicate whether the biomedical includes the presence or lack of the condition.

Examples described herein relate to automatic identification and transformation of a color region. A user can identify a region of a video frame or image that corresponds to a color region that is to be segmented. A color region can include one or more colors that appear to be approximately a uniform color. For one or more video frames, gamma correction can be applied to frames of the video. One or more frames of a video can be mapped to two color spaces. For each pixel in an image, a determination is made if the pixel has the same color as that of the identified region based on each of the at least two color spaces identifying the pixel as the color. The color region can be identified throughout a video and transformed to another color to aid in video editing.

Provided are various mechanisms and processes for automatic computer vision-based defect detection using a neural network. A system is configured for receiving historical datasets that include training images corresponding to one or more known defects. Each training image is converted into a corresponding matrix representation for training the neural network to adjust weighted parameters based on the known defects. Once sufficiently trained, a test image of an object that is not part of the historical dataset is obtained. Portions of the test image are extracted as input patches for input into the neural network as respective matrix representations. A probability score indicating the likelihood that the input patch includes a defect is automatically generated for each input patch using the weighted parameters. An overall defect score for the test image is then generated based on the probability scores to indicate the condition of the object.

The present disclosure provides methods and apparatus for evaluating tissue structure in damaged or healing tissue. The present disclosure also provides methods of identifying a patient at the onset of risk of pressure ulcer or at risk of the onset of pressure ulcer, and treating the patient with anatomy-specific clinical interventions selected, based on thermal imaging (TI). The present disclosure also provides methods of stratifying groups of patients based on risk of wound development and methods of reducing incidence of tissue damage in a care facility. The present disclosure also provides methods to analyze trends of TI intensities to detect tissue damage before it is visible, and methods to compare bisymmetric TI intensities to identify damaged tissue.