Abstract: Methods of training a machine learning model and using the trained model to assess ultrasound measurement data are disclosed. In one arrangement, training data comprises a plurality of classified frames of ultrasound measurement data. Each of at least a subset of the classified frames is classified as representing an imaging plane capable of providing information about a respective target anatomical feature. First and second samples of frames are selected. A machine learning model derives prototype feature vectors from the first sample and feature vectors from the second sample. A loss function depending on metrics representing distances between the feature vectors and the prototype feature vectors is optimized to train the machine learning model.

Abstract: A system and method are provided to automatically categorize biological and medical images. The new system and method can incorporate a machine learning classifier in which novel ideas are provided to guide the classifier to focus on regions of interest (ROI) within medical images for categorizing or classifying the images. The system and method can ignore regions when misleading structures exist. The detection and classification of one or more features of interest within a discriminative region of interest within an image are rendered invariant to differences in translation, orientation and/or scaling of the one or more features of interest within the medical image(s). The system and method allow a processor to more quickly, efficiently and accurately process and categorize medical images.

Abstract: A system and method are provided to automatically categorize biological and medical images. The new system and method can incorporate a machine learning classifier in which novel ideas are provided to guide the classifier to focus on regions of interest (ROI) within medical images for categorizing or classifying the images. The system and method can ignore regions when misleading structures exist. The detection and classification of one or more features of interest within a discriminative region of interest within an image are rendered invariant to differences in translation, orientation and/or scaling of the one or more features of interest within the medical image(s). The system and method allow a processor to more quickly, efficiently and accurately process and categorize medical images.

Abstract: A method of transforming a three-dimensional ultrasound Doppler image that represents flow within a subject uses a three-dimensional ultrasound intensity image that has a common field of view and represents structure within the subject. Within the three-dimensional structural image, there is identified a three-dimensional reference surface that represents the location of a surface of the structure represented by the three-dimensional structural image. A mapping is derived that maps the three-dimensional surface into a two-dimensional plane. The mapping is applied to map the three-dimensional surface of the flow image at the location represented by the three dimensional reference surface into a two-dimensional flow image.

Abstract: A method for processing a sequence of images. In an embodiment, one or more training datasets are analyzed having a sequence of images showing a first condition and a sequence of images showing a second condition. A multivariate regression model is used to determine a relationship between relative positions of one or more features in the sequence of images showing the first condition and relative positions of the one or more features in the sequence of images showing the second condition. In an embodiment, the determined relationship is used to predict positions of the one or more features in an inquire sequence of images showing the second condition given an inquire sequence of images showing the first condition. The predicted positions can then be refined using various methods. In an embodiment, sequences of images are aligned to a common time scale.

Abstract: A method for processing a sequence of images. In an embodiment, one or more training datasets are analyzed having a sequence of images showing a first condition and a sequence of images showing a second condition. A multivariate regression model is used to determine a relationship between relative positions of one or more features in the sequence of images showing the first condition and relative positions of the one or more features in the sequence of images showing the second condition. In an embodiment, the determined relationship is used to predict positions of the one or more features in an inquire sequence of images showing the second condition given an inquire sequence of images showing the first condition. The predicted positions can then be refined using various methods. In an embodiment, sequences of images are aligned to a common time scale.

Abstract: The invention provides for the visualisation of conventional and parametric images of materials as they are progressively distorted during examination. A conventional image is displayed simultaneously alongside one or more parametric images derived from the original image data, with the parametric images displaying mechanical properties such as elasticity and mobility. The mobility values are calculated from the tracking error obtained from a motion or strain estimation algorithm applied to a sequence of image frames. The values of elasticity and mobility are displayed in a colour overlay on the conventional image background and the transparency of the overlay is varied according to the parameter values to de-emphasise less relevant values.

Abstract: A plurality of images of a common object acquired by ultrasound echo imaging, such as echocardiography, are combined. In respect of each image, a monogenic signal is derived and used to derive, in respect of each pixel, feature measures being measures of phase congruency feature, and alignment measures being measures of the degree of alignment between the normal to said phase congruency feature and the analysis beam. In respect of each pixel, there are derived relative weights for the plurality of images in correspondence with the feature measures for the plurality of images in respect of the corresponding pixel, taking into account the alignment measures for the plurality of images. A combined image is produced by combining the corresponding pixels of each image in accordance with the determined relative weights.

Abstract: An image processing technique which identifies pixels in images which are associated with features having a selected shape, such as but not exclusively step edge, roof, ridge or valley. The shape of the intensity profile in the image is compared in an intensity independent way with a shape model to select those pixels which satisfy the shape model and are thus associated with the feature of interest. This comparison is achieved by examining the phase and amplitude of a spectral decomposition of parts of the image profile in the spatial or spatio temporal frequency domain. This decomposition can be achieved using quadrature wavelet pairs such as log-Gabor wavelets. The difference between the odd and even components, known as the feature asymmetry, gives an indication of the shape of the feature. The analysis may be extended to the time domain by looking at the shape of the image profile across a time sequence of images, which gives an indication of the velocity of a moving feature.

Abstract: A method of analysing a sequence of images of a deformable object in non-rigid motion involves modeling the boundary using a non-rigid contour. A representation of movement of the contour through the sequence of images is calculated using a tracking space shape. The calculated movement representation is decomposed using an interpretational space shape that is different than the tracking space shape.

Abstract: A composition including a photoresist formulation and a surfactant additive is described herein.

Abstract: An ultrasound apparatus and method of ultrasound examination in which the contact force between the ultrasound probe and the subject is measured and recorded. Because contact between the ultrasound probe and the subject deforms the underlying tissue, recordal of the contact force allows the deformation to be calculated. Then an inverse deformation can be calculated and used to correct the received signals to generate the signals which would have been obtained if there had been no contact between the ultrasound probe and the subject. The deformation of the subject may be predicted using a model, such as a finite element model.

Abstract: An image processing technique which identifies pixels in images which are associated with features having a selected shape, such as but not exclusively step edge, roof, ridge or valley. The shape of the intensity profile in the image is compared in an intensity independent way with a shape model to select those pixels which satisfy the shape model and are thus associated with the feature of interest. This comparison is achieved by examining the phase and amplitude of a spectral decomposition of parts of the image profile in the spatial or spatio temporal frequency domain. This decomposition can be achieved using quadrature wavelet pairs such as log-Gabor wavelets. The difference between the odd and even components, known as the feature asymmetry, gives an indication of the shape of the feature. The analysis may be extended to the time domain by looking at the shape of the image profile across a time sequence of images, which gives an indication of the velocity of a moving feature.