9 results about "Mineral density" patented technology

Described are systems and methods to determine one or more regional body composition values for one or more regions of a body based on a processing of one or more two-dimensional images that include a representation of the body. Regional body composition values may include any of a fat tissue mass, a lean muscle mass, a bone mineral density, a skeletal muscle mass, etc., which may be determined for any one or more regions of the body, such as the right arm, left arm, right leg, left leg, trunk, android, gynoid, etc.

The utility model relates to a bone mineral density ultrasonic detection device which comprises an adjusting seat fixedly arranged on a bottom plate and a calcaneus bone mineral density instrument arranged on the bottom plate in a left-right sliding mode, a seat is arranged on the adjusting seat, and the seat can be adjusted in the inclination direction of a leg placing plate in the calcaneus bone mineral density instrument. The front end of the seat face of the seat extends towards the calcaneus bone densitometer to form a supporting plate, and the supporting plate and the leg placing plate are parallel to each other and are arranged in an aligned mode. The bone mineral density ultrasonic detection device is convenient to use, the shanks can be just naturally attached to the supporting plate by adjusting the front-back position of a detected person on the seat surface, and due to the fact that the supporting plate is just aligned with a leg placing plate on the calcaneus bone mineral density instrument, the soles of the detected person can be tightly attached to a foot placing plate by adjusting the height of the seat, and the detection accuracy is improved. Therefore, the feet of the detector can be stably placed, and the problem that the detection result is inaccurate due to the fact that the detector exerts improper force and the feet are placed incorrectly is solved.

The present application provides methods of use, specifically methods of treatment of a disease, disorder, or condition (e.g, a low bone mass condition such as osteoporosis) in a human individual, comprising administration of novel bispecific antibodies that bind to both sclerostin and DKK-1 (e.g, anti-Sclerostin x anti-DKK-1 bispecific antibodies). The present application also provides methods of increasing bone mineral density in a human individual comprising administration of novel anti-Scl erostin x anti-DKK-1 bispecific antibodies. The present application further provides methods of reducing risk of bone fracture (e.g., osteoporotic fracture) in a human individual comprising administration of novel anti-Sclerostin x anti-DKK-1 bispecific antibodies.

The invention discloses a coal rock density calculation method, device and equipment. The method comprises the following steps: firstly, acquiring total rock mineral X diffraction experiment data, X-ray element data of target position coal rock, coal rock average porosity and coal rock average water saturation; obtaining the ash content mineral type of the coal rock according to the total rock mineral X diffraction experiment data; calculating the type of the ash mineral and the mass fraction of the organic matter mineral by utilizing the mass fraction of the characteristic element in the ash mineral and the X-ray element data; calculating the skeleton density of the coal rock by using the mineral density of the coal rock, the ash content mineral type and the mass fraction of the organic matter mineral; and calculating the density data of the coal rock at the target position by using the average porosity of the coal rock, the average water saturation of the coal rock and the skeleton density of the coal rock. In the process, after X-ray element data is obtained on a drilling site, a series of element calculation is carried out, the density data of the coal rock at the target position can be obtained, the calculation method is simple, and the requirement for timeliness while drilling is met.

The invention provides a metallurgical mineral conveying process component real-time monitoring method and a metallurgical mineral conveying process component real-time monitoring system based on electromagnetic tomography. The method comprises the following steps: carrying out non-contact scanning on a conveyor belt by adopting a multi-frequency excited and eccentrically arranged EMT sensor array, and constructing a mineral-electromagnetic characteristic mapping database in combination with an electromagnetic tomography image reconstruction algorithm and a deep learning method; real-time mineral pixel-level identification is carried out through the trained machine learning model; the recognition result is divided according to grid areas, and the real-time mass ratio data of all minerals on the material section are calculated in combination with the pre-calibrated mineral density and the area weight factor corrected by the belt curvature; and signal drift compensation is carried out by fusing high-precision temperature sensor data. And finally, real-time mass ratio data are converted into control signals, downstream equipment such as a sorting mechanical arm and a batching valve is driven, online recognition, precise quantification and intelligent regulation and control of mineral components are achieved, and the resource utilization efficiency and the automation level in the metallurgical process are remarkably improved.

The invention belongs to the technical field of mineral density measurement, and particularly discloses a heavy mineral density measurement method and system, and the measurement method comprises the following steps: obtaining the resonant frequency offset detected by a piezoelectric ceramic sensor; according to the resonant frequency offset and a predetermined mass sensitivity constant, calculating the mass of the heavy mineral sample according to a Sauerbrey formula; acquiring a plurality of two-dimensional images obtained by performing multi-angle image acquisition on the heavy mineral sample by a microscope; based on the plurality of two-dimensional images, generating a three-dimensional model of the heavy mineral sample through a three-dimensional reconstruction algorithm, and calculating the volume of the heavy mineral sample; the three-dimensional reconstruction algorithm comprises feature point matching and alignment, sparse point cloud generation, dense point cloud generation and surface grid construction; calculating the density of the heavy mineral sample according to the mass and the volume. According to the invention, high-precision density measurement of the heavy mineral sample with small size and irregular shape can be realized.

This invention discloses a dynamic image analysis and measurement method and system for cassiterite mineral particles, specifically relating to the field of industrial vision analysis technology. It addresses the problem that existing methods struggle to accurately distinguish particle motion states and separate motion trails in dynamic flow fields, leading to inaccurate segmentation, tracking, and parameter measurement. By acquiring continuous frame images and extracting flow velocity characteristics of the flow field region, the method determines cross-frame displacement trends based on the overlap of neighboring pixel grayscale distribution and flow velocity characteristics. It extracts the stability of candidate particle contour morphology and performs matching verification. For matched particles, it constructs a flow velocity field constraint range and obtains a motion vector field. Combining the motion vector amplitude corresponding to the cassiterite mineral density, it uses density clustering to distinguish cross-frame displacement from independent multi-particle motion. High-speed moving particles are selected, and inter-frame grayscale gradient difference is used to separate motion trails from the true contour. Based on the motion type and the true contour, it completes target segmentation, contour tracking, and parameter measurement, improving the accuracy of particle analysis under dynamic conditions.

This invention discloses a method and system for longitudinal bone mineral density prediction and high-risk window identification, belonging to the field of intelligent bone health assessment technology. Based on a large amount of localized population-based bone mineral density data assets, this invention preprocesses the data to construct a regionally adaptive dual-graph LSTM network for temporal bone mineral density prediction. It quantifies prediction uncertainty and generates confidence intervals using a Bayesian method, employs the PELT algorithm to detect bone mineral density evolution change points, and identifies the critical point of accelerated decline. By integrating prediction results, confidence intervals, and change point locations, a three-dimensional high-risk window is delineated, and personalized intervention plans are output, supporting multi-platform deployment. This invention solves the problems of inapplicability to traditional assessment standards, difficulty in capturing nonlinear changes, and insufficient prediction reliability, significantly improving the accuracy of bone mineral density prediction and the timeliness of clinical intervention. It is suitable for osteoporosis risk screening and primary healthcare management.

The present disclosure provides methods of treating patients having decreased bone mineral density, methods of identifying subjects having increased risk of developing decreased bone mineral density, methods of detecting human Zinc And Ring Finger 3 (ZNRF3) variant nucleic acid molecules and variant polypeptides, and ZNRF3 variant nucleic acid molecules and variant polypeptides.