57 results about "Reviewing Radiologist" patented technology

A marking device for defining the margins and orientation of radiography specimens includes a plurality of visually distinctive markers joined by a base that holds the markers until the markers are secured to a specimen. The base serves as a holder for the individual markers as the markers are secured to a specimen with sutures or staples, at which time the markers are disconnected from the base. One or more markers may be secured to a specimen as needed to define the orientation of the specimen. By securing markers to specific locations on a specimen, a surgeon can indicate to radiologists and pathologists the specimen's orientation in the body before removal, thus aiding in future study of the specimen. Since the markers are made either wholly or partially from radiopaque material, the markers are visible when radiographed.

A system for the automatic generation of custom report viewing utilizes imaging data and computer-aided detection technology to identify cancerous tumors. A typical collection of data from a patent's scan may include hundreds of images and associated data. The custom report viewer allows one physician, such as a radiologist, to analyze the data and prepare a report. The generated report may contain images, computed measurements, classifications based on a standard (such as the ACR BI-RADS for Breast MR), and locations relative to landmarks. Different physicians, such as an oncologist or a surgeon, may have need of differing images and supporting data for their own purposes. Each physician may select, in advance, custom selection criteria that are stored in association with that physician. A report generator module uses the stored selection criteria and report filtering to extract the images and supporting data specified by the particular physician. The system allows a surgeon to alter the selection criteria and obtain further images if necessary and permits the generation of multiple selection criteria by one physician for different purposes, such as surgical planning, therapy reporting, and the like.

The invention discloses a breast lump image feature extraction method based on edge neighborhood weighing. The breast lump image feature extraction method mainly solves the problem that in the prior art, extracted features do not contain the edge neighborhood local features of a breast lump. The breast lump image feature extraction method comprises the steps of (1) inputting an image, (2) adjusting the size of the breast lump image which is input, (3) extracting a lump edge, (4) determining the number of inner indentation pixel points and the number of outer extension pixel points, (5) determining the inner region of a lump which undergoes inner indentation, (6) determining the inner region of the lump which undergoes outer extension, (7) obtaining an edge neighborhood image of the breast lump, (8) obtaining weighing values, (9) extracting scale invariant features, (10) extracting word bag features and (11) obtaining features of the breast lump image which undergoes edge neighborhood weighing. By means of the breast lump image feature extraction method, expression of the features of the breast lump image are more robust, the image features are expressed more effectively, the benign and malignant classification accuracy of lumps is improved, and therefore doctors in the radiology department can be assisted in conducting medical diagnosis.

A method and system for computer-aided detection of abnormal lesions in digital mammograms is described, wherein digital films are processed using an automated and computerized method of detecting the order and orientation of a set of films. In one embodiment, anatomic features are used to detect the order, orientation and identification of a film series. In another embodiment of the invention, a technologist feeds films into the system in any order and orientation. After processing, the system provides an output on a display device to a radiologist that is in an order and orientation preferred by the radiologist. In yet another embodiment of the invention, films from one case are distinguished from films of another case. In this manner and through the use of a bulk loader, a large number of films can be stacked together and fed into the system at one time.

Computerized methods, systems, and user interfaces for handling one or more radiology orders are provided. Such methods, systems, and user interfaces allow a radiologist, radiological technician, or other healthcare professional to efficiently review and approve, modify, or reject electronic requests from ordering physicians to have patients undergo radiological examination. Such methods, systems, and user interfaces also allow regulators to audit the radiology vetting process to ensure that proper review of radiological examination requests is being conducted. Computerized methods, systems, and user interfaces for automatic electronic notification of ordering physicians of modified or cancelled radiological examination requests are also provided.

A system and method to increase the efficiency and effectiveness of a radiologist. A display protocol for medical imaging equipment may allow a plurality of three-dimensional medical images to be concurrently displayed and navigated. The three-dimensional medical images may be linked so a user can manipulate the viewing angle and pointer in the linked images. The display protocol can be configured to display a three-dimensional image from a current exam and a three-dimensional comparison image. Moreover, a display protocol for medical imaging equipment may allow at least one three-dimensional medical image to be concurrently displayed with at least one two-dimensional medical image. The three-dimensional medical image may be linked with the two-dimensional medical image so a user can manipulate the viewing angle and pointer in the linked images. The display protocol can be configured to display a three-dimensional image with axial, sagital, coronal, or non-standard oblique views.

The invention discloses a mammary gland molybdenum target X-ray image block feature extraction method based on tower-shaped principal component analysis (PCA). The mammary gland molybdenum target X-ray image block feature extraction method based on tower-shaped PCA mainly overcomes the defect that features extracted in the prior art do not contain the feature that the density of the middle of a lump is large while the density of the edge of the lump is small. The method comprises the following steps of (1) carrying out pretreatment, (2) constituting a tower-shaped structure, (3) obtaining a gray feature vector of each image layer, (4) training a feature space of the gray feature of each image layer, (5) obtaining principal component features of each image layer, and (6) obtaining mammary gland molybdenum target X-ray image block features based on tower-shaped PCA. According to the method, the mammary gland molybdenum target X-ray image block features can be represented more robustly, image features can be represented more effectively, the accurate rate of detection of a lump region in a mammary gland molybdenum target X-ray photography image is increased, and therefore radiologists are assisted to carry out clinical diagnosis.

Cone Beam Breast CT (CBBCT) is a three-dimensional breast imaging modality with high soft tissue contrast, high spatial resolution and no tissue overlap. CBBCT-based computer aided diagnosis (CBBCT-CAD) technology is a clinically useful tool for breast cancer detection and diagnosis that will help radiologists to make more efficient and accurate decisions. The CBBCT-CAD is able to: 1) use 3D algorithms for image artifact correction, mass and calcification detection and characterization, duct imaging and segmentation, vessel imaging and segmentation, and breast density measurement, 2) present composite information of the breast including mass and calcifications, duct structure, vascular structure and breast density to the radiologists to aid them in determining the probability of malignancy of a breast lesion.

The invention relates to a medical image automatic segmentation method based on deep learning, and provides a solution for challenges such as complex imaging background, lack of shape features, intensity specificity and position priori in a tumor or organ segmentation task, so that automatic positioning and segmentation of a tumor or an organ are realized. Specifically, a segmentation strategy based on a region of interest is designed, a sparse target detection module is used to automatically position and classify tumors or organs, and mask branches are used to finely segment the region of interest. In addition, boundary segmentation is fused into mask segmentation to obtain a finer segmentation result. The invention aims at solving the limitation of a conventional semantic segmentation method in tumor or organ segmentation tasks, and solving the problem of working efficiency of radiologists to a certain extent and reducing manual wrong segmentation caused by personal deviation and clinical experience by realizing full-automatic tumor or organ segmentation.

According to the attributes of notification targets such as patients, radiology doctors, and nurses, information owned by medical imaging apparatuses is provided in appropriate timing to improve a workflow of hospitals. A dispatch agent being a software component is executed on a processor of a medical imaging apparatus. Different types of observer terminals (cellular phones, etc.) in which observer agents conforming to the attributes of notification targets operate register information (event) desired for notification in the dispatch agent. The dispatch agent monitors various processing processes being executed in the processor, and on detecting the occurrence of a registered event, notifies the observer terminals of its occurrence. Since the dispatch agent is also a sort of processes executed in the processor, network traffic is not increased by its monitoring of various processing processes.

The invention discloses a management method and platform for an acute cerebral apoplexy first-aid process, and belongs to the technical field of medical first-aid. The intelligent bracelet is introduced; First-aid personnel bind the smart bracelet through the App and upload patient information. after receiving the information through the App, the doctors in the hospital carry out first-aid early warning in advance; An on-duty doctor, a thrombolysis nurse, a radiologist, a clinical laboratory doctor and an interventional doctor App mobile terminal carry out high-efficiency dispersion in each link of an in-hospital first-aid process in a task distribution mode, and an intelligent bracelet automatically senses key node time and uploads the key node time through an App to finally complete thewhole process of acute cerebral apoplexy first-aid. According to the invention, resources in necessary fields of the acute cerebral apoplexy first-aid link are more comprehensively integrated, complete closed-loop linkage is realized, an efficient first-aid process is provided, and the medical rescue level can be greatly improved.

A radiology workstation (10) includes a computer (12) connected to access radiology studies stored in an radiology studies archive (20) with at least one processor (22) programmed to operate the computer to: provide a user interface (24) for performing readings of radiology studies including: displaying images on a display (14) of a current radiology study being read; receiving user inputs via one or more user input devices (16) and operating on the user inputs to manipulate the display of images and to open and view past radiology studies during the reading and to receive a radiology report summarizing the reading and store the radiology report in the radiology studies archive; and recording a activity log of user inputs received via the one or more user input devices during readings of radiology studies. While providing the user interface for performing a reading by a radiologist of a current radiology study of a patient, tire at least one processor is Anther programmed to perform a relevant past radiology study recommendation process including: identifying at least one previously-read radiology study of the patient stored in the radiology studies archive as being relevant to the current radiology study of the patient using a radiologist-specific relevance identification criterion derived from content of the activity log recording the radiologist opening and viewing past radiology studies during readings performed by the radiologist; and displaying an indication of the at least one relevant previously-examined radiology study on the display.

The invention discloses a mammary gland molybdenum target X-ray image block feature extraction method based on tower-shaped principal component analysis (PCA). The mammary gland molybdenum target X-ray image block feature extraction method based on tower-shaped PCA mainly overcomes the defect that features extracted in the prior art do not contain the feature that the density of the middle of a lump is large while the density of the edge of the lump is small. The method comprises the following steps of (1) carrying out pretreatment, (2) constituting a tower-shaped structure, (3) obtaining a gray feature vector of each image layer, (4) training a feature space of the gray feature of each image layer, (5) obtaining principal component features of each image layer, and (6) obtaining mammary gland molybdenum target X-ray image block features based on tower-shaped PCA. According to the method, the mammary gland molybdenum target X-ray image block features can be represented more robustly, image features can be represented more effectively, the accurate rate of detection of a lump region in a mammary gland molybdenum target X-ray photography image is increased, and therefore radiologists are assisted to carry out clinical diagnosis.