39 results about "Palpable mass" patented technology

The invention discloses an X-ray breast mass image automatic classification method. According to the invention, an automatic classification network for the X-ray breast mass image is designed from theperspective of image processing; according to the network, firstly, two computing paths are used for carrying out convolution and downsampling operation on an X-ray breast mass image by using convolution kernels of different sizes, convolution feature maps of different scale types are extracted, the feature maps input by the two computing paths are superposed and fused, and feature information obtained after double computing paths are fused is obtained. Feature extraction is carried out on the fusion features by using a full convolutional network, and finally the extracted features are sent to a Softmax classification layer to classify the features, and a breast mass image classification result is obtained. A model is trained by using a membership-based objective function suitable for X-ray breast mass image classification, and a new objective function enhances the generalization ability of the model by increasing the membership degree of a breast mass sample and a category to which the breast mass sample belongs and reducing the membership degree of the breast mass sample and a non-category to which the breast mass sample belongs, so that the classification accuracy is improved.

A transducer is used to send an ultrasound pulse toward a stone and to receive ultrasound reflections from the stone. The recorded time between a pulse that is reflected from the proximal surface and a pulse that is reflected either from the distal surface of the stone or from a surface supporting the stone is used to calculate the stone size. The size of the stone is a function of the time between the two pulses and the speed of sound through the stone (or through the surrounding fluid if the second pulse was reflected by the surface supporting the stone). This technique is equally applicable to measure the size of other in vivo objects, including soft tissue masses, cysts, uterine fibroids, tumors, and polyps.

The invention belongs to the technical field of medical image processing, and provides a breast cancer image information bottleneck multi-task classification and segmentation method and system. The method comprises the following steps: acquiring a plurality of breast images of contrast enhanced X-ray photography and corresponding benign and malignant categories and lump position pixel-level labels; performing preprocessing operation on each acquired breast image of the contrast enhanced X-ray photography; adopting a multi-task network to extract multi-task shared representation for each preprocessed mammary gland image; inputting the shared representation to a classification encoder to obtain an encoding tensor of an intermediate layer, and then sending the intermediate encoding tensor to an information bottleneck attribution module for feature compression and benign and malignant classification to obtain a classification task tensor; adapting the shared representation to a segmentation network to obtain a segmentation task tensor; and carrying out feature fusion on the classification task tensor and the segmentation task tensor to segment the focus.

Embodiments of the present application provide a method and device for detecting breast X-ray image masses, electronic equipment and a computer-readable storage medium, and solve the problem of low accuracy of a current method for detecting breast X-ray image masses. The method for detecting the breast X-ray image masses includes the following steps: inputting an axial breast X-ray image and a lateral oblique breast X-ray image into a mass detection model; determining coordinate data of a mass contour of the axial breast X-ray image and coordinate data of a mass contour of the lateral obliquebreast X-ray image; determining the coordinate of a center point of the axial breast mass and the coordinate of a center point of the lateral oblique breast mass; obtaining the coordinate of an axialnipple and the coordinate of a lateral oblique nipple; calculating the axial nipple and breast distance according to the coordinate of the center point of the axial breast mass and the coordinate of the axial nipple, and calculating the lateral oblique nipple and breast distance according to the coordinate of the center point of the lateral oblique breast mass and the coordinate of the lateral oblique nipple; and confirming that the axial breast X-ray image mass and the lateral oblique breast X-ray image mass are the same breast mass.

The invention provides a breast lump image segmentation method and system based on pruning U-Net + +, and relates to the technical field of ultrasonic image segmentation. The constructed pruning U-Net + + breast lump image segmentation model is based on a U-Net + + network, feature expressions of all branch U-Net are fused through jump connection, residual connection is introduced to replace dense connection in the U-Net + + method, and an obtained original breast ultrasound image is segmented through the model. According to the constructed pruning U-Net + + breast ultrasound image segmentation model, when the lumps in the breast ultrasound image are segmented, the model overfitting problem caused by the small data set problem of medical image data can be avoided, and the generalization ability of the ultrasound image breast lump segmentation model is improved; meanwhile, the scale of the model parameters is far smaller than that of the prior art, the complexity of the network model is reduced, the calculation time of network training can be shortened, the memory occupation of network training is reduced, and the model training efficiency is improved.

The invention discloses a simulation device for mammary gland rotary cutting needle or puncture needle training under ultrasound, and relates to interventional instruments such as rotary cutting needles and puncture needles, the simulation device comprises an outer skin, a filler, a simulation lump, a bottom plate and an anti-skid module, the outer skin is arranged on the upper surface of the bottom plate, the filler is arranged in the outer skin, the simulation lump is arranged in the filler, and anti-skid modules are symmetrically mounted on the lower surface of the bottom plate. According to the invention, the tissue texture can be simulated under the ultrasonic image, and under the observation of the ultrasonic image, the tumor implantation can realistically simulate the ultrasonic image of the breast benign mass. A rotary cutting needle or a puncture needle can be used for excision, no obvious needle passage or cavity is left in an ultrasonic image when the rotary cutting needle or the puncture needle is pulled out, the real simulation of training is improved, the hardness of the simulated lump is controlled to show a water-containing solid under ultrasound, and the simulated lump can be cut off by the rotary cutting needle or the puncture needle and pulled out through a negative pressure pipeline.

The invention discloses a breast cancer marking ruler and a marking technology, and relates to the technical field of breast cancer marking, in particular to a breast cancer marking ruler and a marking technology. The breast cancer marking ruler comprises a transverse measuring ruler, a surveying and mapping ruler arranged on the transverse measuring ruler and a groove clamping plate arranged on the surveying and mapping ruler, and the groove clamping plate is integrally fixed to the surveying and mapping ruler; a plurality of measuring scales are engraved on the transverse measuring scale and the surveying and mapping scale, two limiting mechanisms are further arranged on the transverse measuring scale, and supporting rods are arranged at the two ends of the transverse measuring scale. Compared with a guide wire positioning technology and a breast tissue positioning mark clamp technology which are most commonly used at the present stage, the application of the rectangular plane coordinate system breast cancer and cancerous swelling body surface marking method is innovation and supplement; especially for breast cancer which cannot be positioned by iconography examination after puncture biopsy and iconography negative breast cancer which achieves pathological complete remission or nearly pathological complete remission through new adjuvant therapy, the method is one of technologies capable of accurately positioning the primary lump position before an operation.

The invention provides a breast screening system based on infrared thermal imaging, which comprises an infrared thermal imager, a system host and a display, the infrared thermal imager is connected with the system host through a USB connecting line, the system host transmits an infrared image of the infrared thermal imager to the display for displaying, the breast screening system further comprises a shell, an examination space with an outlet is enclosed by the shell, a user enters a detection space for examination, an outlet of the detection space is provided with a shielding curtain, the shielding curtain is used for sealing the outlet, and the shell is further provided with an air conditioning system. According to the invention, the privacy during screening can be ensured, so that an examinee can perform screening in a relatively comfortable environment, the influence of factors such as temperature, wind speed and background can be overcome, the screening efficiency is improved, the accuracy is also improved, the breast can be preprocessed, tiny breast masses can be accurately screened, the screening accuracy is increased further. The breast screening system is reasonable in structural design, convenient and fast to use and high in practicability.

The invention relates to an auxiliary device for breast mass excision, and belongs to the technical field of medical instruments. The device comprises: an X-shaped support; two multi-stage telescopic plates which are symmetrically arranged at one end of the X-shaped support and used for being attached to a tissue layer at the breast incision; and a distraction assembly arranged at the other end of the X-shaped support and used for driving the multi-stage telescopic plates to move towards the two sides to distraction the mammary gland incision. A supporting plate and the X-shaped support form a distraction plane, the supporting plate is attached to the tissue layer of the incision, and the newly cut tissue layer is distraction in time along with continuous incision of the tissue layer, so that the situation that an operating table is crowded due to the fact that multiple persons use operating forceps for traction is avoided, the operation speed is increased, and the work intensity of doctors is reduced; in addition, tissue layer tearing caused by traction of the operating forceps can be avoided, and unnecessary injury to a patient is avoided; and the device is easy to operate, convenient to use, high in practicability and worthy of popularization.

The invention provides a multi-modal feature fusion Vnet-based breast mass segmentation method. The method comprises the following steps: S1, obtaining a breast magnetic resonance image and a data set of breast mass segmentation results manually marked by a doctor; s2, data preprocessing: dividing data in the data set; s3, constructing a network model based on multi-modal feature fusion Vnet; s4, training the network model in the step S3, and performing parameter adjustment to obtain a predicted breast lump segmentation result; and S5, comparing the predicted breast lump segmentation result obtained in the step S4 with the breast lump segmentation result manually marked by the doctor in the step S1 by using a set evaluation index and a loss function, and verifying the effectiveness of the segmentation method. The breast mass segmentation accuracy can be effectively improved, doctors are assisted in diagnosis and decision making, the burden of the doctors is relieved, and the method has high application value in breast mass auxiliary diagnosis, operation simulation and medical teaching.

The invention discloses a breast lump segmentation method based on deep learning. According to the scheme, a deep neural network is trained by training a manually labeled lump image. After a complete mammary gland image is input, the network can autonomously learn imaging features of the lumps, and an output result is an area which is identified as the lumps by the network, so that end-to-end mammary gland lump segmentation is realized. In order to improve the detection rate of the lumps, the invention discloses a novel weighted compound loss function.

Aiming at the fact that the existing breast lesion detection algorithm cannot well combine the information of bilateral breasts, cannot simultaneously meet the needs of identification and detection of multiple diseases including lumps and calcifications, and has a general effect on asymmetric dense glands, the present invention proposes A fully convolutional single-stage mammography lesion detection method with fusion of multi-image information. Use a non-anchor-based method for lesion detection, extract features of different scales from the original image, fuse the features of different scales, and fuse the information of different images, and finally directly predict whether a point on the feature map corresponds to a lesion and the specific location of the lesion.

The invention provides a visual follow-up visit system and method based on breast ultrasonic scanning, and relates to the technical field of medical treatment. The system specifically comprises a datacollection module which is used for collecting and processing three-dimensional lump positioning images and obtaining current follow-up visit information of a patient so as to configure an identification code for the patient; a central storage module which is connected with the data collection module and is used for storing the three-dimensional lump positioning images and the follow-up visit information in a classified manner according to the identification code; and a data analysis module which is connected with the central storage module and used for extracting the three-dimensional lump positioning images and the follow-up visit information, carrying out alignment superposition on the three-dimensional lump positioning images according to the follow-up visit information to obtain superposed images, processing the superposed images to obtain lump change data and displaying the lump change data in real time. The system has the beneficial effects that through three-dimensional reconstruction of a mammary gland image, a doctor can master the illness state and conduct lump annotation positioning, and the three-dimensional lump positioning images of the patient with the same identification code can be extracted for multiple times, so that lump changes are visually reflected, and follow-up visit advises are checked and provided.