Search results for "Digital mammography"

showing 4 items of 4 documents

Evaluation of DR and CR digital mammography systems based on phantom and breast dosimetry.

2006

Digital mammography has been progressively introduced in screening centers, since recent evolution of CR and DR detectors. However, it is questionable which exposure conditions would be more suitable when these techniques are applied, in order to reduce the glandular breast doses, as they are related with induced carcinogenesis. Several exposures have been performed in CR and DR mammography units for comparing absorbed doses during quality control assessments and during screening, diagnosis and treatment. In the first case, the CIRS11A mammographic phantom has been used with standard exposure conditions (28 kV, AEC mode with blackening +0, 50:50 glandularity and 4.5 compressed breast thickn…

Quality Controlmedicine.medical_specialtyDigital mammographyImage qualityBreast NeoplasmsRadiation DosageImaging phantommedicineMammographyDosimetryHumansMedical physicsRadiometrymedicine.diagnostic_testbusiness.industryComputersPhantoms ImagingEquipment DesignRadiographic Image EnhancementClinical diagnosisReference valuesRadiographic Image EnhancementFemaleNuclear medicinebusinessSoftwareMammographyConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference
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A novel solution based on scale invariant feature transform descriptors and deep learning for the detection of suspicious regions in mammogram images.

2020

Background: Deep learning methods have become popular for their high-performance rate in the classification and detection of events in computer vision tasks. Transfer learning paradigm is widely adopted to apply pretrained convolutional neural network (CNN) on medical domains overcoming the problem of the scarcity of public datasets. Some investigations to assess transfer learning knowledge inference abilities in the context of mammogram screening and possible combinations with unsupervised techniques are in progress. Methods: We propose a novel technique for the detection of suspicious regions in mammograms that consist of the combination of two approaches based on scale invariant feature …

lcsh:Medical technologyclassificationlcsh:R855-855.5computer-assisted image processingdigital mammographydeep learningOriginal Articlecomputing methodologiesClassification computer‐assisted image processing computing methodologies deep learning digital mammography
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Computer-aided diagnosis in digital mammography: comparison of two commercial systems

2014

Aim: Within this work, a comparative analysis of two commercial computer-aided detection or diagnosis (CAD) systems, CyclopusCAD® mammo (v. 6.0) produced by CyclopusCAD Ltd (Palermo, Italy) and SecondLook® (v. 6.1C) produced by iCAD Inc. (OH, USA) is performed by evaluating the results of both systems application on an unique set of mammographic digital images routinely acquired in a hospital structure. Materials & methods: The two CAD systems have been separately applied on a sample set of 126 mammographic digital cases, having been independently diagnosed by two senior radiologists. According to the human diagnosis, the cases in the sample reference set are divided into 61 negatives and 6…

Pathologymedicine.medical_specialtyDigital mammographyRadiological and Ultrasound Technologymedicine.diagnostic_testbusiness.industryCad systemSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Digital imageComputer-aided diagnosisBreast cancer clusters computer-assisted diagnosis FFDM FROC curve mammografy mass lesions microcalcifications performancemedicineMammographyRadiology Nuclear Medicine and imagingRadiologybusiness
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Lesion Segmentation in Breast Sonography

2010

Sonography is gaining popularity as an adjunct screening technique for assessing abnormalities in the breast This is particularly true in cases where the subject has dense breast tissue, wherein widespread techniques like Digital Mammography (DM) fail to produce reliable outcomes This article proposes a novel and fully automatic methodology for breast lesion segmentation in B-mode Ultra-Sound (US) images by utilizing region, boundary and shape information to cope up with the inherent artifacts present in US images The proposed approach has been evaluated using a set of sonographic images with accompanying expert-provided ground truth.

Ground truthmedicine.medical_specialtyLesion segmentationDigital mammographybusiness.industryBreast lesionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONmedicine.diseaseBreast sonographyBreast cancerFully automaticmedicineComputer visionSegmentationRadiologyArtificial intelligencebusiness
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