The present invention extends to methods, systems, and computer program products for predicting embryo implantation probability. A neural network accesses a set of images depicting an embryo. The neural network determines a correlation between the set of images and images corresponding to other embryos considered during neural network training. The neural network derives an embryo implantation probability associated with the embryo based on known implantation outcomes associated with the other embryos and in view of clinical data associated with a potential recipient of the embryo. An embryo is selected for the potential recipient based at least in part on the derived embryo implantation probability. The neural network can also derive a confidence and/or explanation of why the neural network assigned an embryo implantation probability to an embryo. The confidence can be considered in embryo selection.

An ultrasound diagnostic apparatus according to an embodiment includes a processing circuitry. The processing circuitry acquires first image data that is image data obtained during the ultrasound scan executed on the object and that is image data before the coordinate conversion corresponding to the format of the ultrasound scan. The processing circuitry uses the trained model generated through the learning using the first image data obtained during the previously executed ultrasound scan and the area including the object in the first image data to estimate the area in the acquired first image data.

Systems and methods are provided for determining a clinical parameter representing the location of interest within a reproductive cellular structure. An image of the reproductive cellular structure is obtained and provided to a neural network to generate the clinical parameter. The clinical parameter is stored on a non-transitory computer readable medium.

Disclosed are systems, devices, and methods for detecting characteristics of an unhatched egg. A set of images of an unhatched egg are obtained, where each of the spectral images is obtained in a particular wavelength range. The set of images is processed to extract image features, where the image features includes an image texture feature. The extracted image features are processed to classify the unhatched egg according to at least one characteristic. The at least one characteristic may include fertility and/or gender.

A computer-implemented system and method for predicting female sex bovine offspring to result from a bovine embryo by processing video image data of the embryo. The method includes receiving image data derived from video of a target embryo taken at substantially real-time frame speed during an embryo observation period of time. The video contains recorded morphokinetic movement of the target embryo occurring during the embryo observation period of time. The movement is represented in the received image data and the received image data is processed using a model generated utilizing machine learning and correlated embryo outcome data.

A system and method for providing a guided workflow through a series of ultrasound image acquisitions with reference images updated based on a determined anatomical position is provided. The method includes acquiring and displaying, by an ultrasound system, at least one ultrasound image of an anatomy. The method includes determining, by at least one processor, a position of the anatomy depicted in the at least one ultrasound image. The method includes automatically selecting and displaying, by the at least one processor, reference images corresponding to pre-defined views of an ultrasound examination. An orientation of anatomy depicted in the selected and displayed reference images is based on the determined position of the anatomy. The method includes acquiring and displaying, by the ultrasound system, additional ultrasound images of the anatomy corresponding to the selected and displayed reference images. The additional ultrasound images include pre-defined views of the ultrasound examination.

Provided are an ultrasound diagnosis apparatus and a method of displaying an ultrasound image. The ultrasound diagnosis apparatus includes: one or more processors configured to acquire ultrasound image data with respect to a fetus and generate an ultrasound image based on the ultrasound image data; a display configured to display the ultrasound image; and an input interface configured to receive position type information, wherein the one or more processors are further configured to determine positions of organs in the ultrasound image based on the position type information and control the display to display information about the organs together with the ultrasound image, based on the determined positions.

Systems and methods are provided for provided for automatic evaluation of a human embryo. An image of the embryo is obtained and provided to a neural network to generate a plurality of values representing the morphology of the embryo. The plurality of values representing the morphology of the embryo are evaluated at an expert system to provide an output class representing one of a current quality of the embryo, a future quality of the embryo, a likelihood that implantation of the embryo will be successful, and a likelihood that implantation of the embryo will result in a live birth.

A frequency offset is selected based on similarity measures of multiple MRI images obtained from frequency scout measurements associated with multiple frequency offsets from a reference frequency of a magnetization excitation pulse. The similarity measure for each respective MRI image of the multiple MRI images is determined based on a comparison between at least one reference image and the respective MRI image. The at least one reference image is determined from the multiple MRI images based on spectrum information of each of the multiple MRI images. Such methods facilitate automatically determining/selecting a more optimal frequency offset for an MRI scan following a frequency scout scan, in particular, for an SSFP or a bSSFP pulse sequence, and thereby banding artifacts and/or flow-related artifacts can be reduced for the MRI scan.

Systems and methods are provided for fully automated screening for aneuploidy in a human embryo. An image of the embryo is obtained at an associated imager and provided to a neural network to generate a first clinical parameter. A set of at least one parameter representing one of biometric parameters of one of a patient receiving the embryo, an egg utilized to produce the human embryo, a sperm used to create the embryo, a sperm donor who provided sperm used to create the embryo, and an egg donor who provided the egg is retrieved, and a second clinical parameter is generated from the set of at least one parameter at a predictive model. A composite parameter, representing a likelihood of aneuploidy in the embryo, is generated from the first clinical parameter and the second clinical parameter.