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US 10,646,156 B1Granted
Adaptive image processing in assisted reproductive imaging modalities
AssigneeCycle Clarity, LLC
InventorJohn Anthony Schnorr
Life of this patent
Estimating the term…
Abstract
Adaptive image processing, image analysis, pattern recognition, and time-to-event prediction in various imaging modalities associated with assisted reproductive technology. The reference image may be processed according to one or more adaptive processing frameworks for de-speckling or noise processing of ultrasound images. The subject image is processed according to various computer vision techniques for object detection, recognition, annotation, segmentation, and classification of reproductive anatomy, such as follicles, ovaries and the uterus. An image processing framework may also analyze secondary data along with subject image data to analyze time-to-event progression of the subject image.
Claims20
A computer-aided diagnostic and predictive image processing system for the clinical management of infertility through assisted reproductive technology, the system comprising:
- an imaging sensor operable to execute a three-dimensional (3D) ultrasound to collect one or more 3D images of a reproductive anatomy of a patient;
- a storage device for storing, locally or remotely, the one or more 3D images of the reproductive anatomy of the patient;
- and
- at least one processor operably engaged with at least one computer-readable storage medium storing computer-executable instructions thereon that, when executed, cause the processor to perform one or more actions, the one or more actions comprising:
- receiving the one or more 3D images of the reproductive anatomy of the patient;
- processing the one or more 3D images of the reproductive anatomy of the patient to detect one or more reproductive anatomical structures and annotate one or more anatomical features of the one or more reproductive anatomical structures;
- analyzing the one or more anatomical features according to at least one non-linear framework to predict at least one time-to-event outcome, wherein the at least one non-linear framework comprises an artificial neural network selected from a convolutional neural network and a fully convolutional neural network and the at least one time-to-event outcome comprises an egg retrieval date from the patient for in vitro fertilization;
- and
- generating at least one graphical user output in response to the at least one time-to-event outcome prediction, the at least one graphical user output corresponding to one or more recommended clinical actions for the clinical management of infertility in the patient.
6 more elements
A computer-aided diagnostic and predictive image processing system for the clinical management of infertility through assisted reproductive technology, the system comprising:
- an imaging sensor operable to execute one or more imaging modalities to collect one or more digital images of a reproductive anatomy of a patient, wherein the one or more imaging modalities comprise a three-dimensional (3D) ultrasound, the one or more digital images comprise one or more 3D ultrasound images, and the reproductive anatomy comprises an ovarian anatomy of the patient;
- an artificial intelligence engine configured to receive, locally or remotely, the one or more digital images of the reproductive anatomy of the patient, and to process the one or more digital images of the reproductive anatomy of the patient and to generate at least one time-to-event outcome prediction according to at least one non-linear framework, wherein the at least one non-linear framework is selected from the group consisting of a convolutional neural network, a recurrent neural network, a fully convolutional neural network, a dilated residual network, a generative adversarial network and combinations thereof, and the at least one time-to-event outcome prediction comprises an optimal egg retrieval date for in vitro fertilization;
- an electronic medical record database comprising one or more longitudinal medical records of one or more patients undergoing infertility treatment with assisted reproductive technology, the electronic medical record database being configured to communicate medical record data of the one or more patients undergoing infertility treatment with assisted reproductive technology to the artificial intelligence engine such that the medical record data is incorporated into the at least one non-linear framework;
- an outcome database comprising one or more longitudinal records of clinical outcomes of one or more patients undergoing infertility treatment with assisted reproductive technology, the outcome database being configured to communicate clinical outcomes data of the one or more patients undergoing infertility treatment with assisted reproductive technology to the artificial intelligence engine such that the clinical outcomes data is incorporated into the at least one non-linear framework, wherein the clinical outcomes data relates to a success rate of embryo implantation and pregnancy following in vitro fertilization;
- an application server operably engaged with the artificial intelligence engine to receive the one or more 3D digital images of the reproductive anatomy of the patient, the medical record data, the outcomes data, and the at least one time-to-event outcome prediction, the application server executing an application configured to generate one or more recommended clinical actions for the clinical management of infertility through assisted reproductive technology in response to the at least one time-to-event outcome prediction, the one or more recommended clinical actions comprising a recommended time of egg retrieval from the patient;
- and
- a user device communicably engaged with the application server, the user device being configured to display a graphical user interface containing the one or more recommended clinical actions for the clinical management of infertility.
4 more elements
A computer-readable storage medium encoded with computer-executable instructions for commanding one or more processors to execute operations of a method for predicting at least one time-to-event outcome based on one or more ultrasound images of a reproductive anatomy of a patient and one or more patient phenotypes obtained from a patient medical record, the operations comprising:
- receiving one or more ultrasound images of a reproductive anatomy of a patient;
- receiving one or more patient medical records from an electronic medical record database, the one or more patient medical records comprising stored longitudinal medical records of one or more patients undergoing infertility treatment through assisted reproductive technology;
- processing the one or more ultrasound images of the reproductive anatomy of the patient to detect one or more reproductive anatomical structures and annotate one or more anatomical features of the one or more reproductive anatomical structures;
- processing the patient medical record of the one or more patients undergoing infertility treatment through assisted reproductive technology to identify one or more patient phenotypes, the one or more patient phenotypes being selected from the group consisting of ovulation, anovulation, oligo ovulation, endometriosis, male factor infertility, tubal factor infertility, and decreased ovarian reserve;
- analyzing the one or more anatomical features and the one or more patient phenotypes according to at least one non-linear framework, the non-linear framework comprising a convolutional neural network;
- and
- predicting the at least one time-to-event outcome according to the at least one non-linear framework, the at least one time-to-event outcome prediction comprising an optimal egg retrieval date from the patient for in vitro fertilization.
4 more elements
Dependencies are inferred from the claim text.