Search results for "Mr images"

showing 4 items of 14 documents

Disease Biomarkers: Modelling MR Spectroscopy and Clinical Applications

2012

Clinical MRS has become a reference technique for in vivo evaluating the metabolism of different tissues, with special application to brain and prostate lesion characterization and tumour’s follow-up. It allows detecting relevant changes that cannot be appreciated in the conventional MR images. Nowadays, MRS has been widely applied in many different brain pathologies with excellent results as a disease biomarker. Since the different diseases and grades have different manifestations in the spectroscopic profile, a deep understanding of the subjacent biology is needed for the signal interpretation. The development of high-field (≥3 T) scanners has permitted the acquisition of high-quality MRS…

Signal interpretationIn vivo magnetic resonance spectroscopymedicine.medical_specialtymedicine.diagnostic_testbusiness.industryMagnetic resonance imagingmedicine.diseaseProstate cancermedicine.anatomical_structureProstatemedicineDisease biomarkerRadiologyMr imagesbusinessFat fraction
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Automatic multi-seed detection for MR breast image segmentation

2017

In this paper an automatic multi-seed detection method for magnetic resonance (MR) breast image segmentation is presented. The proposed method consists of three steps: (1) pre-processing step to locate three regions of interest (axillary and sternal regions); (2) processing step to detect maximum concavity points for each region of interest; (3) breast image segmentation step. Traditional manual segmentation methods require radiological expertise and they usually are very tiring and time-consuming. The approach is fast because the multi-seed detection is based on geometric properties of the ROI. When the maximum concavity points of the breast regions have been detected, region growing and m…

business.industryComputer scienceComputer Science (all)Pattern recognitionImage segmentationGold standard (test)Breast MR030218 nuclear medicine & medical imagingTheoretical Computer Science03 medical and health sciencesSeed detection0302 clinical medicineRegion of interestRegion growing030220 oncology & carcinogenesisManual segmentationSegmentationSensitivity (control systems)Artificial intelligenceAutomatic segmentationMr imagesbusinessMaximum concavity point
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Focal liver lesions hyperintense on T1-weighted magnetic resonance images.

2009

This article reviews focal liver lesions hyperintense on T1-weighted magnetic resonance (MR) images and describes the underlying etiologies associated with their T1 signal intensity. Although focal liver lesions are commonly detected because of their iso- or hypointensity on T1-weighted images, lesions (benign or malignant) may present with T1 hyperintensity when they contain T1 shortening elements--such as fat, hemorrhage, copper, melanin, and highly concentrated proteins. Our discussion includes the description of state-of-the-art T1-weighted MR sequences and the imaging features of lesions on pre- and postcontrast MR images that are characteristic for lesion composition and useful for ma…

medicine.medical_specialtymedicine.diagnostic_testbusiness.industryLiver DiseasesContrast MediaMagnetic resonance imagingMagnetic Resonance ImagingHyperintensityLesionDiagnosis DifferentialImaging Three-DimensionalmedicineT1 weightedHumansRadiology Nuclear Medicine and imagingRadiologySignal intensityMr imagesmedicine.symptombusinessNuclear medicineSeminars in ultrasound, CT, and MR
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Differentiation between brain metastases and glioblastoma multiforme based on MRI, MRS and MRSI

2009

Brain metastases and glioblastoma multiforme are the most aggressive and common brain tumours in adults and they require a different clinical management. Anatomical magnetic resonance imaging (MRI) or clinical history, cannot always clearly distinguish between them. This study describes and verifies the use of magnetic resonance spectroscopy (MRS) and magnetic resonance spectroscopic imaging (MRSI) in combination with MRI for differential diagnosis of glioblastomas and metastases. Feature selection methods are applied to the magnetic resonance (MR) spectra of 121 patients and relevant features are detected. Different classification methods are used to distinguish glioblastoma multiforme and…

medicine.medical_specialtymedicine.diagnostic_testbusiness.industryMagnetic resonance spectroscopic imagingMagnetic resonance imagingmedicine.diseaseMetastasisClinical historymedicineRadiologyDifferential diagnosisMr imagesbusinessBrain metastasisGlioblastoma
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