69 results about "Department radiology" patented technology

A computer-aided diagnostic method and system provide image annotation information that can include an assessment of the probability, likelihood or predictive value of detected or identified suspected abnormalities as an additional aid to the radiologist. More specifically, probability values, in numerical form and / or analog form, are added to the locational markers of the detected and suspected abnormalities. The task of a physician using such a system as disclosed is believed to be made easier by displaying markers representing different regions of interest.

A method, system and computer readable medium for an intelligent search display into which an automated computerized image analysis has been incorporated. Upon viewing an unknown mammographic case, the display shows both the computer classification output as well as images of lesions with known diagnoses (e.g., malignant vs. benign) and similar computer-extracted features. The similarity index used in the search can be chosen by the radiologist to be based on a single feature, multiple features, or on the computer estimate of the likelihood of malignancy. Specifically the system includes the calculation of features of images in a known database, calculation of features of an unknown case, calculation of a similarity index, display of the known cases along the probability distribution curves at which the unknown case exists. Techniques include novel developments and implementations of computer-extracted features for similarity calculation and novel methods for the display of the unknown case amongst known cases with and without the computer-determined diagnoses.

X-ray mammography has been the standard for breast cancer screening for three decades, but offers poor statistical reliability; it also requires a radiologist for interpretation, employs ionizing radiation, and is expensive. The combination of multiple independent tests, performed effectively at the same time and co-registered, can produce substantially more reliable detection performance than that of the individual tests. The multi-sensor approach offers greatly improved reliability for detection of early breast tumors, with few false positives, and also can be designed to support machine decision, thus enabling screening by general practitioners and clinicians; it avoids ionizing radiation, and can ultimately be relatively inexpensive.

A web-based system is disclosed for managing radiology services for one or more medical facilities. The system, comprising both hardware and software components, provides mechanisms by which radiographic images and demographic information about a patient are transmitted to a central location and efficiently combined, allowing a designated radiologist to efficiently interpret the radiographic images and produce a preliminary report. The central location includes web-based, secure access by which multiple entities may interpret and update the preliminary report. Although the system is designed with after-hours radiology services in mind, the system may be employed in radiology departments during regular weekday operation.

The invention relates to the field of medical image processing and pattern recognition, and provides a computer-assisted lump detecting method based on a mammary gland magnetic resonance image. The computer-assisted lump detecting method based on the mammary gland magnetic resonance image aims at solving the problems that in the prior art, the lump partition effect is not good, and the accuracy, the sensitivity and the specificity in a classification test are not high. The computer-assisted lump detecting method includes the following steps: S1, extracting an interest area from the mammary gland magnetic resonance image; S2, extracting an initial lump area from the interest area in a separated mode, and determining the contour line of the initial lump area; S3, calculating the weight distribution of characteristic parameters of the initial lump area; S4, selecting the characteristic parameters, with the weight coefficients larger than a standard weight coefficient, of the initial lump area, and carrying out training classifying to obtain optimized characteristic parameters; S5, inputting the optimized characteristic parameters into a classifier, analyzing the optimized characteristic parameters with a support vector machine classification method, determining a final lump area, and displaying the final lump area for a user. The detecting method has the good lump partition effect, the accuracy, the sensitivity and the specificity in the classification test are effectively improved, the detecting result serves as a second opinion to be provided for a radiologist, and the misdiagnosis rate and the missed diagnosis rate of the radiologist can be effectively reduced.

A method of detecting and diagnosing cancers characterized by the presence of at least one nodule / neoplasm from an imaging scan is presented. To detect nodules in an imaging scan, a 3D CNN using a single feed forward pass of a single network is used. After detection, risk stratification is performed using a supervised or an unsupervised deep learning method to assist in characterizing the detected nodule / neoplasm as benign or malignant. The supervised learning method relies on a 3D CNN used with transfer learning and a graph regularized sparse MTL to determine malignancy. The unsupervised learning method uses clustering to generate labels after which label proportions are used with a novel algorithm to classify malignancy. The method assists radiologists in improving detection rates of lung nodules to facilitate early detection and minimizing errors in diagnosis.

An automatic method for the registration of prone and supine computed tomographic colonography data is provided. The method improves the radiologist's overall interpretation efficiency as well as provides a basis for combining supine / prone computer-aided detection results automatically. The method includes determining (centralized) paths or axes of the colon from which relatively stationary points of the colon are matched for both supine and prone positions. Stretching and / or shrinking of either the supine or prone path perform registration of these points. The matching and registration occurs in an iterative and recursive manner and is considered finished based on one or more decision criteria.

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.

The invention discloses to a multi-parameter MRI prostate cancer CAD method and system based on two kinds of classifiers, relating to the medical image processing field. The multi-parameter MRI prostate cancer CAD method comprises candidate focus automatic detection and candidate focus computer aided diagnosis. The candidate focus automatic detection comprises steps of respectively performing pre-processing on three MRI sequences of each case: T2WI, DWI, ADC to make resolution ratios and sizes of the T2WI, the DWI, the ADC identical, wherein pixels of a same position basically correspond to a same part of a human body, and respectively extracting point characteristics on three kinds of MRI sequences of each case, and inputting the point characteristics into a focus detection classifier to obtain a candidate focus. The candidate focus computer aided diagnosis comprises steps of calculating regional characteristics of the candidate focus in three kinds MRI sequences of each case and inputting the regional characteristics into a focus diagnosis classifier to obtain a corresponding diagnosis result. The multi-parameter MRI prostate cancer CAD method and system based on two kinds of classifiers can provide a series of quantized indexes and a malignant probability value.

A method and system for the use of a CAD algorithm that can be used to automatically detect retained colonic fluid and the rectal tube in computed tomographic (CT) imagery of a patient's colon is disclosed. The CAD algorithm can then electronically subtract the fluid and rectal tube from the images and the modified CT imagery can then be displayed to a user, such as a radiologist. Both the original and modified CT imagery will be stored for future presentation and review. The user, including the radiologist or other medical personnel, will have the option to toggle between displaying and reviewing the modified and original imagery. After subtraction, the radiologist will be able to view the imagery containing all pertinent information regarding the colonic lumen and any suspect region within the colon. Additionally, full processing of the scan is possible even when fluid retention in the colon is greater than fifty percent in any region.

The invention relates to a method for transmitting image for radiological department in hospital. The invention employs medical image device, image receiving module, image storage module, image standardized module, hospital information system interface, storage inquiry management module, image managing system PACS interface to transmit image for hospital radiological department, which is characterized by convenient management, prolonged storage time and fast inquiry.

Occasionally relevant findings and important recommendations made within medical or radiology reports fail to elicit the appropriate follow-up due to multiple factors. The clinician may miss the recommendation or lose track of it while addressing a more acute illness, the recommendation may have not been conveyed to the patient, or the patient may fail to schedule or show-up for the subsequent exam. Prior literature indicates that a significant percentage of scheduled appointments result in no-shows or cancellations by patients, and a small but significant percentage of indicated follow-up studies are thus not obtained. Such omissions occasionally result in adverse consequences suffered by the patients, and increase the risk of legal liabilities to the clinicians or radiologists. A method and system is presented that identifies patients who did not obtain such recommended diagnostic tests or therapeutic interventions, and which sorts and filters the detected patients according to relevance of the recommendation, optionally discarding recommendations of low relevance, and facilitates the management of the detected patients.

A two step platform elevates a standing patient upon a horizontally located chamber for examination of the foot and ankle by radiological methods. The chamber receives a slide that carries an x-ray film beneath a foot of a standing patient. Additionally, the patient stands upon a visually and radiologicaly transparent deck. The deck has one slot for upright positioning and a chamber for horizontal positioning of a radiological film cartridge. The platform of the present invention allows a radiologist to take a radiological image of a patient's foot and ankle from both the side and above.

The invention relates to the field of medical image technology, and particularly to a breast nodules auxiliary diagnosis method based on DSSD and a system. The system comprises a breast image workstation, a breast cloud diagnosis system and a breast diagnosis mobile terminal. The breast image workstation performs breast image acquisition. The breast cloud diagnosis system comprise training set anda testing set preprocessing, marking and neural network discriminating, wherein the training set and the testing set preprocessing comprises multi-scale image de-noising and enhancing. The method comprises the steps of acquiring a breast graph by the breast image workstation, performing discriminating through mainly using a DSSD neural network, and finally transmitting a result which is obtainedthrough processing of the breast cloud diagnosis system to the breast diagnosis mobile terminal. According to the method and the system, a computer-aided diagnosis (CAD) system based on deep learningis developed for aiming at the field of the medical image (unnatural image), thereby supplying a second opinion for diagnosis to a radiology department doctor, and more effectively assisting the doctor in performing diagnosis.

The invention relates to a diagnostic imaging instrument for radiology department, and belongs to the technical field of medical instrument. The diagnostic imaging instrument for radiology department comprises a diagnostic imaging instrument main body, a radiological imaging device and an examining table sliding device, wherein an information interaction wire hole is arranged on the diagnostic imaging instrument main body; an information interaction wire extends out of the information interaction wire hole; the information interaction wire is connected to a plug slot by virtue of a movable plug; an information processing plate is arranged on the lower side of the plug slot; a diagnostic imaging device is arranged on the lower side of the information processing plate; universal wheel fixed legs are arranged on the lower side of the diagnostic imaging device; the lower sides of the universal wheel fixed legs are connected to universal wheel connecting rods; and the lower sides of the universal wheel connecting rods are connected to universal wheel fixing devices. The diagnostic imaging instrument disclosed by the invention is complete in function and convenient to use; and the diagnostic imaging instrument, when conducting radiological diagnosis on patients, is scientific and effective, simple and practical, safe and reasonable, time-saving and labor-saving, and the instrument is capable of relieving working difficulty of doctors.

Disclosed is a clinical stereoscopic imaging examination device in radiology department including bottom plate, the horizontal section of the bottom plate is circular, the upper surface of the bottomplate and the lower surface of the rotating disk are rotatably connected by a planar bearing, axis of planar bearings, axis of base plate, the axes of the rotating disk coincide, the lower surface ofthe bottom plate is fixed with a stepping motor through a fixing bracket, the output shaft and the lower end of the rotation shaft of the stepping motor are connected through a coupling. The upper endof the rotating shaft passes through the perforation of the bottom plate and is fixed coaxially with the lower surface of the rotating circular plate, the patient stands on the rotating circular plate, the feet of the patient clamp the limiting rod, and the back of the patient leans against the vertical plate, so that the position of the patient is fixed when the rotating circular plate stands, the patient stands in a standard manner, the detection accuracy is improved, and the work efficiency of the doctor is improved. The physician can adjust the shortest distance between the vertical plateand the center of the rotating plate according to the patient's body shape, so as to improve the applicability of the clinical stereoscopic imaging examination device of the radiology department.

The invention discloses a medical imaging assistance device used in the radiology department. The medical imaging assistance device comprises a base, wherein a scanner body is fixed to the left side face of the base, a bed body is connected to the upper side face of the base in a sliding mode, a control switch is installed on the front side face of the bed body, the input end of the control switch is connected with the output end of an external power supply, and two horizontal fixing shafts are oppositely fixed in the inner cavity of the bed body. The medical imaging assistance device used in the radiology department is simple in structure and convenient to adjust and corresponds to a reference line on the scanner body by arranging six groups of adjusting belts in the bed body to transversely adjust the body of a patient and turning the adjacent adjusting belts in a staggered mode to adjust local bending of the body, fixing and separation of a single gear sleeve and a rotary shaft can be achieved through a bidirectional driving air cylinder, the corresponding gear sleeve is driven to rotate through the rotary shaft so as to achieve adjusting belt adjustment, control is convenient, detection abnormity caused by an incorrect prone position is avoided, and the burden of a doctor is relieved.

The invention relates to a network browsing method for treating image for hospital radiological department, which employs medical image device, image browsing module, image transmission module, radiological information system and internet for image in radiological department to be browsed on internet. The invention is characterized by convenient usage and low cost.

The invention discloses a radiology department-used lifting-type special platform, which comprises a supporting box body. The supporting box body is internally provided with an electric control device; the right side inside the supporting box body is provided with a storage device; the bottom plate of the supporting box body is provided with all-around wheels; stiffeners are arranged on the supporting box body; the middle of the supporting box body is provided with a lifting device; four corners of the working platform are welded with guiding cylinders connected onto the bottom part of the bed body via sliding vertical columns; the rear end of the bed body is provided with a cal button; the front end of the call button is provided with a telescopic transfusion stand; the right end of the bed body is provided with a medical pillow; the right end of the bed body is provided with the working platform; and a sound player is arranged on the vertical supporting plate of the working platform. The radiology department-used lifting-type special platform adopts leadscrew nut pairs to realize lifting and replaces the existing hydraulic lifting device, leakage of hydraulic fluid is avoided, the platform is clean and pollution-free, a patient can call a doctor at any time during the treatment process as the call button is set, the device considers the feelings of the patient, and the actual demands can be met.

The invention discloses a medical inspection test bed for a radiology department. The medical inspection test bed comprises a radiology test bed and a fixed arm. A radiation-proof glass cover is internally provided with an X ray tube. The surface of the medical inspection test bed is connected to a bracket through a fixed hinge. The top of the bracket is connected to a lighting lamp through a movable hinge. The middle part of the left edge of the radiology test bed is connected to a drawer through a fixed end, and the middle part of the right edge of the radiology test bed is connected to a distribution box through a fixed end. The upper end of the fixed arm is connected to the radiology test bed through a fixed hinge, the right surface of the fixed arm is provided with a power supply switch, and the end of the lower side of the fixed arm is connected to a support base through a fixed hinge. The support base is fixed to the surface of the fixed base. The medical inspection test bed for a radiology department has the advantages of a simple structure and convenience in use, the operation in examining a patient is simple, and the working difficulty of medical personnel is reduced.

A method and system for medical image pre-processing at the medical image scanner that facilitates joint interpretation of the medical images by radiologists and artificial intelligence algorithms is disclosed. Raw medical image data is acquired by performing a medical image scan of a patient using a medical image scanner. Input data associated with the medical image scan of the patient and available downstream automated image analysis algorithms is acquired. A set of pre-processing algorithms to apply to the raw medical image data is selected based on the input data associated with the medical image scan of the patient and the available downstream automated image analysis algorithms using a trained machine learning based model. One or more medical images are generated from the raw medical image data by applying the selected set of pre-processing algorithms to the raw medical image data.

The invention discloses a clinical three-dimensional imaging examination device for the radiology department. The device comprises a base, a high pressure generator is arranged at the left side of theupper surface of the base, and a starting switch is arranged on the portion, close to the high pressure generator, of the left side of the upper surface of the base; a supporting rack is arranged atthe right side of the upper surface of the base, a PLC is arranged at the upper end of the supporting rack, and an illumination switch is arranged on the portion, close to the supporting rack, of theupper surface of the base; a cylinder body is arranged in the middle of the upper surface of the base, guide rails are vertically arranged at the left and right sides of the bottom in the cylinder body, and linear motors are slidingly clamped to the side surfaces of the guide rails; an annular rack is arranged between the two linear motors, a fixing plate is arranged at one side in the annular rack, and a mounting groove is formed in the side surface of the fixing plate; an X-ray tube is arranged in the mounting groove, and a connection plate is arranged at the other side in the annular rack.The clinical three-dimensional imaging examination device for the radiology department is convenient to use, a patient can be quickly subjected to whole-body scanning examination, step-by-step multi-term examination is not needed, and the working efficiency of medical personnel is improved.

An artificial intelligence engine for directed hypothesis generation and ranking uses multiple heterogeneous knowledge graphs integrating disease-specific multi-omic data specific to a patient or cohort of patients. The engine also uses a knowledge graph representation of ‘what the world knows’ in the relevant bio-medical subspace. The engine applies a hypothesis generation module, a semantic search analysis component to allow fast acquiring and construction of cohorts, as well as aggregating, summarizing, visualizing and returning ranked multi-omic alterations in terms of clinical actionability and degree of surprise for individual samples and cohorts. The engine also applies a moderator module that ranks and filters hypotheses, where the most promising hypothesis can be presented to domain experts (e.g., physicians, oncologists, pathologists, radiologists and researchers) for feedback. The engine also uses a continuous integration module that iteratively refines and updates entities and relationships and their representations to yield higher quality of hypothesis generation over time.

The invention discloses a tumor prediction method for a PET-CT image based on a neural network. The tumor prediction method comprises the following steps: carrying out interpolation processing on a PET image and a CT image, wherein the lengths, widths and thicknesses of the two images are consistent; carrying out a coding process on the PET image and the CT image through a segmentation network, obtaining a PET feature image and a CT feature image, carrying out cascade combination, obtaining a final sample feature map, carrying out weighting on a PET feature part and a CT feature part of the final sample feature map, obtaining a segmentation model, and obtaining a tumor prediction image through the segmentation model; and performing a false positive removal process on the tumor prediction image through a 3D connected domain to obtain a tumor prediction result. The tumor is automatically segmented and identified by using the deep learning technology of the neural network, the suspected tumor tissue can be rapidly identified, the part is directly analyzed by a doctor, and finally, the diagnosis result is determined by the doctor, so that the working efficiency of a radiologist can be greatly reduced, and the tumor identification accuracy is improved.

The invention discloses a contrast agent used in the tumor radiology department. The raw materials include: 2-12 parts of citric acid buffer solution of the contrast agent Omniscan, 20-50 parts of chloroform, and 1-2 parts of dimethyl sulfoxide in parts by weight. , soybean lecithin 30‑100 parts, dilauroyl lecithin 2‑10 parts, dipalmitoyl lecithin 1‑3 parts, cholesterol 1‑10 parts, PEG3000 2‑12 parts, palmitic acid PEG3000 monoester 1‑4 parts, Palmitic acid‑GG peptide 0.5‑1 part. The developer obtained by the invention can significantly reduce the background noise during magnetic resonance imaging, improve the image contrast quality, not only can detect early tumors, but also make the effective observation time of magnetic resonance imaging more than 2 hours.