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MammoScreen® BD is a software application intended for use with compatible full field digital mammography and digital breast tomosynthesis systems. MammoScreen BD evaluates the breast tissue composition to provide an ACR BI-RADS 5th Edition breast density category. The device is intended to be used in the population of asymptomatic women undergoing screening mammography who are at least 40 years old. MammoScreen BD only produces adjunctive information to aid interpreting physicians in the assessment of breast tissue composition. It is not a diagnostic software. Patient management decisions should not be made solely based on analysis by MammoScreen BD.

MammoScreen BD is a software-only device (SaMD) using artificial intelligence to assist radiologists in the interpretation of mammograms. The MammoScreen BD software is to automatically process a mammogram to assess the density of the breasts. For each examination, MammoScreen BD outputs the breast density in accordance with the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) Atlas 5th Edition breast density categories "A" through "D". MammoScreen BD takes as input a folder with images in DICOM formats and outputs a breast density assessment in a form of a JSON file. MammoScreen BD outputs can be integrated with compatible third-party software such as the MammoScreen Web-UI interface, PACS viewer (using DICOM Structured Report or DICOM Secondary Capture SOP Class UIDs), patient worklists, or within reporting software.

MammoScreen® 3 is a concurrent reading and reporting aid for physicians interpreting screening mammograms. It is intended for use with compatible full-field digital mammography and digital breast tomosynthesis systems. The device can also use compatible prior examinations in the analysis. Output of the device includes graphical marks of findings as soft-tissue lesions or calcifications on mammograms along with their level of suspicion scores. The lesion type is characterized as mass/ asymmetry, distortion, or calcifications for each detected finding. The level of suspicion score is expressed at the finding level, for each breast, and overall for the mammogram. The location of findings including quadrant, depth, and distance from the nipple, is also provided. This adjunctive information is intended to assist interpreting physicians during reporting. Patient management decisions should not be made solely based on the analysis by MammoScreen 3.

MammoScreen is a concurrent reading medical software device using artificial intelligence to assist radiologists in the interpretation of mammograms. MammoScreen processes the mammogram(s) and detects findings suspicious for breast cancer. Each detected finding gets a score called the MammoScreen Score™. The score was designed such that findings with a low score have a very low level of suspicion. As the score increases, so does the level of suspicion. For each mammogram, MammoScreen outputs detected findings with their associated score, a score per breast, driven by the highest finding score for each breast, and a score per case, driven by the highest finding score overall. The MammoScreen Score goes from one to ten. MammoScreen is available for 2D (FFDM images) and 3D processing (FFDM & DBT or 2DSM & DBT). Optionally, MammoScreen can use prior examinations in the analysis. MammoScreen can also aid in the reporting process by populating an initial report with chosen findings, including lesion type and position (quadrant, depth and distance to nipple). The results indicating potential breast cancer, identified by MammoScreen, are accessible via a dedicated user interface and can seamlessly integrate into DICOM viewers (using DICOM-SC and DICOM-SR). Reporting aid outputs can be incorporated into the practice's reporting system to generate a preliminary report. Additionally, certain outputs like the case score can be reported into the patient management worklist. Note that the MammoScreen outputs should be used as complementary information by radiologists while interpreting mammograms. For all cases, the medical professional interpreting the mammogram remains the sole decision-maker.

MammoScreen® is intended for use as a concurrent reading aid for interpreting physicians, to help identify findings on screening FFDM and DBT acquired with compatible mammography systems and assess their level of suspicion. Output of the device includes marks placed on findings on the mammogram and level of suspicion scores. The findings could be soft tissue lesions or calcifications. The level of suspicion score is expressed at the finding level, for each breast and overall for the mammogram. Patient management decisions should not be made solely on the basis of analysis by MammoScreen®.

MammoScreen 2.0 automatically processes the four views (one CC and one MLO per breast) of standard screening FFDM or DBT, and outputs a corresponding report on a separate screen, alongside the monitors used for reading. This report is designed to be easily readable with very few interactions required by providing an overall level of suspicion of each exam and giving explicit visual indications when highly suspicious exams are detected. MammoScreen 2.0 detects and characterizes findings on a scale from one to ten, referred to as the MammoScreen score. The score was designed such that findings with a low score have a very low level of suspicion. As the score increases, so does the level of suspicion. Furthermore, MammoScreen 2.0 provides a high level of interpretability. Results are by construction consistent at the finding, breast and mammogram level. A breast takes on the highest score of its detected findings, and the level of suspicion for the exam is driven by the breast(s) with the highest score. Therefore, it is always possible to track a high suspicion of malignancy for an exam to the corresponding breast(s), and to a specific finding within the breast(s).

MammoScreen™ is intended for use as a concurrent reading aid for interpreting physicians, to help identify findings on screening FFDM acquired with compatible mammography systems and assess their level of suspicion. Output of the device includes marks placed on findings on the mammogram and level of suspicion scores. The findings could be soft tissue lesions or calcifications. The level of suspicion score is expressed at the finding level, for each breast and overall for the mammogram. Patient management decisions should not be made solely on the basis of analysis by MammoScreen™.

MammoScreen is a software-only device for aiding interpreting physicians in identifying focal findings suspicious for breast cancer in screening FFDM (full-field digital mammography) acquired with compatible mammography systems. The product consists of a processing server and a web interface. The software applies algorithms for recognition of suspicious calcifications and soft tissue lesions. These algorithms have been trained on large databases of biopsy proven examples of breast cancer, benign lesions and normal tissue. MammoScreen automatically processes FFDM and the output of the device can be used by radiologists concurrently with the reading of mammograms. The user interface of MammoScreen has several functions: a) Activation of computer aided detection (CAD) marks to highlight locations, known as findings, where the device detected calcifications or soft tissue lesions suspicious for cancer. b) Association of findings with a score, known as the MammoScreen Score, which characterizes findings on a 1-10 scale, with increasing level of suspicion. Only the most suspicious findings (with a MammoScreen score equal or greater than 5) are initially marked to limit the number of findings to review. The user shall also review findings with score of 4 or lower. c) Indication, with matching markers, when findings corresponding to the same findings are detected in multiple views of the FFDM. MammoScreen is configured as a DICOM Web compliant node in a network and receives its input images from another DICOM node, called "the DICOM Web Server". The MammoScreen output will be displayed on the screen of a personal computer compliant with requirements specified in the User Manual. The image analysis unit includes machine learning components trained to detect positive findings (calcifications and soft tissue lesions).