Search results for "Breast ultrasound"

showing 5 items of 5 documents

SIFT Texture Description for Understanding Breast Ultrasound Images

2014

Texture is a powerful cue for describing structures that show a high degree of similarity in their image intensity patterns. This paper describes the use of Self-Invariant Feature Transform (SIFT), both as low-level and high-level descriptors, applied to differentiate the tissues present in breast US images. For the low-level texture descriptors case, SIFT descriptors are extracted from a regular grid. The high-level texture descriptor is build as a Bag-of-Features (BoF) of SIFT descriptors. Experimental results are provided showing the validity of the proposed approach for describing the tissues in breast US images.

medicine.diagnostic_testFeature transformbusiness.industryTexture DescriptorInformationSystems_INFORMATIONSTORAGEANDRETRIEVALComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-invariant feature transformPattern recognitionTexture (geology)ComputingMethodologies_PATTERNRECOGNITIONmedicineDegree of similarityComputer visionArtificial intelligencebusinessBreast ultrasoundMathematics
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Progressi nella caratterizzazione ecografica bi-rads computer-guidata delle lesioni focali mammarie (LFM)

2018

Confrontare la versione 2.0 (V2) con la versione 1.0 (V1) di un software dedicato di supporto decisionale computer-assistito (S-Detect) nella caratterizzazione delle lesioni focali mammarie (LFM))

Breast UltrasoundSettore MED/36 - Diagnostica Per Immagini E Radioterapia
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Diagnostic Performance of an Artificial Intelligence System in Breast Ultrasound.

2021

Objectives We study the performance of an artificial intelligence (AI) program designed to assist radiologists in the diagnosis of breast cancer, relative to measures obtained from conventional readings by radiologists. Methods A total of 10 radiologists read a curated, anonymized group of 299 breast ultrasound images that contained at least one suspicious lesion and for which a final diagnosis was independently determined. Separately, the AI program was initialized by a lead radiologist and the computed results compared against those of the radiologists. Results The AI program's diagnoses of breast lesions had concordance with the 10 radiologists' readings across a number of BI-RADS descri…

medicine.medical_specialtyArtificial Intelligence Systemhealth care facilities manpower and servicesConcordanceeducationBreast Neoplasmsassisted diagnosis (CADx)artificial intelligence (AI)030218 nuclear medicine & medical imagingaided detection (CADe)03 medical and health sciencesbreast cancer0302 clinical medicineBreast cancerArtificial Intelligencehealth services administrationmedicineHumansRadiology Nuclear Medicine and imagingMedical diagnosisBreast ultrasound030219 obstetrics & reproductive medicineRadiological and Ultrasound Technologymedicine.diagnostic_testultrasoundbusiness.industryUltrasoundmedicine.diseasebody regionsmachine learningsurgical procedures operativecomputer‐FemaleRadiologyUltrasonography MammarybusinessJournal of ultrasound in medicine : official journal of the American Institute of Ultrasound in MedicineReferences
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Breast Ultra-Sound image segmentation: an optimization approach based on super-pixels and high-level descriptors

2015

International audience; Breast cancer is the second most common cancer and the leading cause of cancer death among women. Medical imaging has become an indispensable tool for its diagnosis and follow up. During the last decade, the medical community has promoted to incorporate Ultra-Sound (US) screening as part of the standard routine. The main reason for using US imaging is its capability to differentiate benign from malignant masses, when compared to other imaging techniques. The increasing usage of US imaging encourages the development of Computer Aided Diagnosis (CAD) systems applied to Breast Ultra-Sound (BUS) images. However accurate delineations of the lesions and structures of the b…

ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONCAD02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingBI-RADS lexiconOptimization based Segmentation030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineBreast cancerCut0202 electrical engineering electronic engineering information engineeringMedical imagingMedicineComputer visionBreast ultrasound[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingPixelmedicine.diagnostic_testbusiness.industryBreast Ultra-SoundGraph-CutsImage segmentationmedicine.disease3. Good healthComputingMethodologies_PATTERNRECOGNITIONComputer-aided diagnosis020201 artificial intelligence & image processingMachine-Learning based SegmentationArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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RUOLO DI S-DETECT, SISTEMA DI SUPPORTO DECISIONALE COMPUTER-ASSISTITO, NELLA CLASSIFICAZIONE BI-RADS DELLE LESIONI FOCALI MAMMARIE: PERFORMANCE DIAGN…

2018

Breast UltrasoundCADSettore MED/36 - Diagnostica Per Immagini E Radioterapia
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