30 results about "Left lungs" patented technology

The invention discloses a deep learning-based pulmonary fissure segmentation and integrity assessment method and system. Compared with a traditional method, the method has the advantages that the pulmonary fissure segmentation precision and calculation efficiency are obviously improved, and full-automatic pulmonary fissure segmentation and pulmonary fissure integrity assessment are realized. The main steps of the pulmonary fissure segmentation and integrity assessment method comprise: constructing a pulmonary fissure segmentation data set; training a pulmonary fissure segmentation model basedon the full convolutional neural network; predicting a pulmonary fissure area and identifying to obtain left lung oblique fissure, right lung oblique fissure and right lung horizontal fissure; estimating complete pulmonary fissure; evaluating the degree of pulmonary fissure integrity. A full convolutional neural network is adopted; end-to-end pulmonary fissure model training and prediction are realized; the method has the advantages that the prediction speed is high without manual intervention, a segmentation framework from coarse to fine is adopted, the problem that the number of category labels is extremely unbalanced when a full convolutional neural network is used for performing a segmentation task is solved, false positive generated by pulmonary fissure segmentation is removed by introducing pulmonary fissure segmentation, and the pulmonary fissure integrity assessment is more accurate.

The invention relates to the technical field of image processing, in particular to a method and device for calculating the cardiothoracic ratio of a chest medical image. The method comprises the following steps: inputting a chest medical image; obtaining a left lung bounding box, a right lung bounding box and a bounding box of the heart area; extracting a left lung region-of-interest, a right lungregion-of-interest and a heart region-of-interest in the bounding box; determining a minimum bounding box of the lung region of interest according to the left lung region of interest and the right lung region of interest; determining the long axis direction and the transverse axis direction of the human body according to the minimum bounding box of the lung region of interest; Determining a minimum bounding box of the region of interest of the heart; Calculating the ratio of the transverse diameter length of the minimum bounding box of the heart region to the transverse diameter length of theminimum bounding box of the lung, and calculating the ratio of the area of the heart region of interest to the area of the lung region of interest. According to the technical scheme, related tissuescan be accurately segmented, and the cardiothoracic ratio and the cardiothoracic area ratio can be automatically calculated.

The method is suitable for the technical field of computer medical image processing, and provides a three-dimensional lung automatic segmentation and left and right lung separation method based on a CT image, and the method comprises the steps: extracting regions within a preset CT value of the CT image layer by layer from the top to the bottom, and sequentially segmenting the interior and exterior of each layer of region, so as to obtain first segmentation data; sequentially carrying out boundary filling and feature detection on the first segmentation data to obtain a seed point, corresponding to a bronchial trunk, of the CT image; performing adaptive threshold region growth on the seed point according to a predetermined initial high threshold to obtain second segmentation data; and detecting the second segmentation data according to the position characteristics of the bronchus to remove the bronchus, and separating the left lung and the right lung according to the connectivity and morphological characteristics of the left lung and the right lung. The invention further provides a three-dimensional lung automatic segmentation and left and right lung separation system based on the CT image. Therefore, the left lung and the right lung of the CT image can be automatically segmented and separated, the precision is high, and the accuracy is high.

Systems and methods for attenuation compensation in nuclear medicine imaging based on emission data are provided. One method includes acquiring emission data at a plurality of energy windows for a person having administered thereto a radiopharmaceutical comprising at least one radioactive isotope. The method also includes performing a preliminary reconstruction of the acquired emission data to create one or more preliminary images of a peak energy window and a scatter energy window and determining a body outline of the person from at least one of the reconstructed preliminary image of the peak energy window or of the scatter energy window. The method further includes identifying a heart contour and segmenting at least the left lung. The method additionally includes defining an attenuation map based on the body outline and segmented left lung and reconstructing an image of a region of interest of the person using an iterative joint estimation reconstruction.

The invention discloses a right double-lumen bronchial cannula, which comprises a first branch pipe, a second branch pipe, a first air sac and a second air sac. The right double-lumen bronchial cannula is characterized in that the first branch pipe and the second branch pipe are vertically arranged in a clinging manner; the pipe wall of the first branch pipe is fixedly connected with the pipe wall of the second branch pipe; further, upper-end pipe orifices of the first branch pipe and the second branch pipe are flush with each other; a lower-end pipe orifice of the first branch pipe is an inclined plane, and supports the breath of a left lung; a bent branch pipe is arranged at the lower end of the second branch pipe and is moreover located at the lower-end pipe orifice of the first branch; the central axis of the bent branch pipe and the extension axes of the first branch pipe and the second branch pipe are at an angle; the length of the bent branch pipe is 1.5 to 2 centimeters; a pipe orifice of the bent branch pipe is an inclined plane, and supports the breath of a right lung. The first air sac wraps the outer walls of the first branch pipe and the second branch pipe, and closes a main airway. The second air sac wraps the outer wall of the bent branch pipe at the lower end of the second branch pipe, and is used for closing a right main bronchus. The right double-lumen bronchial cannula has the advantages that the resistance during right single-lung ventilation is relieved; meanwhile, the work load of an anesthesiologist is also reduced.

The invention discloses a lung organ model automatic leaf division method based on a CT image. The lung organ model automatic leaf division method comprises the following steps: importing original data ImageData of a chest sequence CT image; extracting a lung parenchyma region by adopting a threshold segmentation algorithm to obtain a binary image of the lung parenchyma, recording the binary image as MASK1, and performing three-dimensional reconstruction on the detected and segmented lung parenchyma region; calculating the maximum bounding box of the pulmonary parenchyma according to whether the outermost boundary of the binary image of the pulmonary parenchyma has a binary point, performing enhancement calculation on the sheet structure to obtain enhanced image data MASK2, further processing to obtain a binary image MASK3, and extracting a set of all points of the left and right binary data as a left lung point cloud S1 and a right lung point cloud S2; performing left lung cutting segmentation by taking the left lung point cloud S1 as input data; and taking the right lung point cloud S2 as input data to sequentially carry out right lung first-stage cutting and right lung second-stage cutting. The method can reduce the interference of the non-lung region on the extraction of the lung gap point cloud, can improve the operation efficiency, does not need manual intervention, and can significantly reduce the workload.

The invention provides a device for demonstrating the harm of smoking to health and a manufacturing method thereof. The device is characterized in that the device is mainly formed by a human body lung model made of plastics, and a smoking pipeline and a support thereof which are connected with the human body lung model, wherein the lung model consists of a transparent and elastic plastics shell and spongy filler wrapped in the shell, materials of the filler in the lung model contain color-changing agent or are coated with color-changing agent on the surface, one end of the smoking pipeline is connected with the lung module, and the other end of the smoking pipeline is branched into a branch pipe A and a branch pipe B. When the device is used, a cigarette is inserted into a round hole at the branch pipe A end and is ignited, the right lung part of the lung model is pinched and released repeatedly for simulating the smoking movement of the human body lungs, and meanwhile, the color of the filler in the right lung part of the lung model is observed to be changed into gray black from red. Through the bright color comparison of the gray right lung part and the ruddy left lung part, the principle and the phenomenon of harm of smoking to the lungs are concretely and visually demonstrated, so that a smoker can personally see the terrible phenomenon of the harm of smoking to the lungs, and is warned of no smoking and quit smoking.

According to the ultrasonic parameter measuring method and the ultrasonic parameter measuring system, the area of a left lung area and / or the area of a right lung area and the head girth are determined respectively based on the obtained four-cavity heart standard section and the thalamus level standard section of a target fetus in the end of diastole, and therefore the lung-head ratio is determined; under the condition that a lump exists in the lung, based on the obtained lung lump area and the thalamus level standard cross section of the target fetus, the size and the head girth of the lung lump area are determined respectively, and therefore the lung-head ratio is determined; the two measurement methods comprise a full-automatic mode and a semi-automatic mode in the whole measurement process, and compared with manual measurement by a user in the prior art, the working efficiency and the measurement accuracy are improved.

The invention discloses a method for cardio-thoracic proportion calculation of a medical image. The method includes steps of acquiring a thorax image; performing segmentation on a lung area in the thorax image and acquiring a left lung image and a right lung image; acquiring the central axis of the left lung and the right lung; measuring a podoid right side maximal cross diameter, a podoid left side maximal cross diameter and a thorax maximal cross diameter; calculating the proportion between the sum of the podoid right side maximal cross diameter and the podoid left side maximal cross diameter and the thorax maximal cross diameter. According to the invention, on the basis of lung segmentation, the podoid maximal cross diameter and the thorax maximal cross diameter are measured automatically and the cardio-thoracic proportion is calculated.

The present invention provides a CT image-based lung lobe segmentation method and device. The method includes the following steps that: a lung region is extracted from a CT image, the lung region is divided into a left lung region and a right lung region; lung lobe crack points are extracted from the left lung region and the right lung region; and a lung lobe crack surface is constructed on the basis of the lung lobe crack points. According to the CT image-based lung lobe segmentation method and device of the invention, the lung region is extracted from the CT image, and the lung region is divided into the left lung region and the right lung region, wherein the left lung region contains two lung lobes, and the right lung region contains three lung lobes; the lung lobe crack points are extracted from the left lung region and the right lung region; and the lung lobe crack surface is constructed on the basis of the lung lobe crack points. With the method and device of the invention adopted, lung lobe segmentation can be automatically performed; after the lung lobe segmentation is performed through the method, if five clear lung lobes cannot be obtained, it can be indicated that physiological abnormalities exist in lungs, or tumors exists around the in the lungs. Since the method can automatically segment the lungs into five lung lobes, if the method fails to obtain five lung lobes through segmentation, it is indicated that the abnormalities exist in the lungs, and therefore, a lot of time can be saved for doctors; and the doctors do not have to spend a lot of time manually analyzing CT images to find suspicious areas.

The invention relates to the technical field of medical image processing, and discloses a method and system for automatically generating a left and right lung three-dimensional model based on a CT image in order to solve the technical problem that existing equipment is low in automation degree, and the method comprises the steps that S1, an original image is acquired and recombined into three-dimensional data; s2, the three-dimensional data are automatically selected for preprocessing, and a secondary image is obtained; s3, segmenting and marking the secondary image to generate a binary image; step S4, generating a Label mark graph of the same peripheral contour ROI, and clearing all pixel values; pixel points are screened, and Label image feature analysis is carried out; s5, extracting a third image from the second image, establishing a corresponding relation, automatically realizing separation of the left lung, the right lung and the bronchial tube, and marking the left lung and the right lung; s6, extracting left and right lung segmentation data; and S7, reconstructing a left and right lung 3D model. The process does not need human interaction intervention, the automation level is improved, and the problem of low automation degree is solved.

The invention provides a CT cervical rib positioning method and system based on atlas registration, and relates to the technical field of image processing. The method comprises the following steps: a bone segmentation step: segmenting a bone structure from a chest CT image, and obtaining bone segmentation masks; a left lung and right lung division step: obtaining bone segmentation masks of a left lung and a right lung from the bone segmentation masks; a coarse registration step: manufacturing rib atlases of the left lung and the right lung, and then respectively registering the rib atlases of the left lung and the right lung to the bone segmentation masks of the left lung and the right lung; a fine registration step: obtaining a tibia mask of left lung bone segmentation and a tibia mask of right lung bone segmentation after coarse registration of the rib structure; a splicing step: splicing the left lung and the right lung, and carrying out logic OR operation on cervical rib masks of the left lung and right lung bone segmentation to obtain cervical rib segmentation masks of the whole lung, so as to complete the positioning of the cervical ribs. According to the invention, the workload of manual labeling can be greatly reduced, and the topological relation of a rib structure in a positioning result can be kept unchanged.

The invention discloses a 3D bronchoscope training model, and belongs to the field of training model structures. Existing training models related to bronchoscope related operation are few in function and inaccurate in model structure. A bronchial tree simulation part, an intermediate lymph node puncture structure simulation part, a lower jaw simulation part and a fixed base are detachably arranged in a camera obscura; the lower jaw simulation part is arranged on the inner bottom surface above the camera obscura, the fixed base is arranged on the inner bottom surface below the camera obscura, the middle lymph node puncture structure simulation part is detachably mounted on the fixed base, one ends of a main trachea simulation part, a right lung trachea simulation part and a left lung trachea simulation part of the bronchial tree simulation part are arranged inside an intermediate lymph node puncture structure simulation part, and the other ends of the main trachea simulation part, the right lung trachea simulation part and the left lung trachea simulation part are located outside the intermediate lymph node puncture structure simulation part; and the convergence end of the lower jaw simulation part is connected to the main trachea simulation part. The training model is fine in structure and convenient to mount and dismount.

The invention relates to the field of medical treatment monitoring, in particular to a method and a system for analyzing correlation between respiration impedance of the left lung and the right lung. The method includes: collecting electrical impedance signals of the left chest part and the right chest part of a testee; subjecting the collected electrical impedance signals to analog-digital conversion to obtain digital signals of electrical impedance of the left chest part and the right chest part; extracting referential characteristic values from the signals of the electrical impedance of the left chest part and the right chest part; analyzing the correlation between the respiration impedance of the left lung and the right lung of the testee. The method and the system have the advantages that the referential characteristic values are extracted according to the signals of the electrical impedance of the left chest part and the right chest part, the correlation between the respiration impedance of the left lung and the right lung of the testee is analyzed according to the referential characteristic values, operation is simple, measured data can be accurately collected quantitatively, good anti-interference effect of the collected signals is achieved, the correlation of the electrical impedance of the left lung and the right lung can be quickly and accurately analyzed, and respiration synchrony of the left lung and the right lung of the testee can be quickly and accurately evaluated.

The invention discloses a lung experiment model system for simulating bioaerosol deposition, which relates to the field of respiratory protection and comprises a bioaerosol exposure experiment cabin,a lung model, a bioaerosol generating and sampling system, a respiratory simulation and monitoring system and the like. A bioaerosol uniform diffuser, a bioaerosol generator and a bioaerosol sampler are mounted at the top of the bioaerosol exposure experiment cabin, the lung model is fixed in a lung model sealed cabin, and the lung model sealed cabin is placed in the middle of the bottom of the bioaerosol exposure experiment cabin; the lung model comprises a left lung transparent flexible model, a right lung transparent flexible model, a transparent throat, a trachea and 2-4 levels of bronchuswhich jointly form a respiratory system model conforming to physiological characteristics of a human body, and the respiratory system model is connected with a bioaerosol sampler and a simulated breathing pump. The system can simulate the deposition and distribution of the biological aerosol in the respiratory system of the human body in a real breathing mode.