0000000000042590

AUTHOR

Maria Gabriella Sabini

showing 16 related works from this author

K-nearest neighbor driving active contours to delineate biological tumor volumes

2019

Abstract An algorithm for tumor delineation in positron emission tomography (PET) is presented. Segmentation is achieved by a local active contour algorithm, integrated and optimized with the k-nearest neighbor (KNN) classification method, which takes advantage of the stratified k-fold cross-validation strategy. The proposed approach is evaluated considering the delineation of cancers located in different body districts (i.e. brain, head and neck, and lung), and considering different PET radioactive tracers. Data are pre-processed in order to be expressed in terms of standardized uptake value, the most widely used PET quantification index. The algorithm uses an initial, operator selected re…

0209 industrial biotechnologyK-nearest neighborComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONFDG and MET PET imagingStandardized uptake value02 engineering and technologyImaging phantomk-nearest neighbors algorithmActive contour algorithm020901 industrial engineering & automationArtificial IntelligenceRegion of interest0202 electrical engineering electronic engineering information engineeringSegmentationElectrical and Electronic EngineeringActive contour modelbusiness.industryProcess (computing)Pattern recognitionCancer segmentationBiological target volumeControl and Systems Engineering020201 artificial intelligence & image processingArtificial intelligencebusinessEnergy (signal processing)Engineering Applications of Artificial Intelligence
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A fully automatic approach for multimodal PET and MR image segmentation in gamma knife treatment planning

2017

The aim of this study is to combine Biological Target Volume (BTV) segmentation and Gross Target Volume (GTV) segmentation in stereotactic neurosurgery.Our goal is to enhance Clinical Target Volume (CTV) definition, including metabolic and morphologic information, for treatment planning and patient follow-up.We propose a fully automatic approach for multimodal PET and MR image segmentation. This method is based on the Random Walker (RW) and Fuzzy C-Means clustering (FCM) algorithms. A total of 19 brain metastatic tumors, undergone stereotactic neuro-radiosurgery, were retrospectively analyzed. A framework for the evaluation of multimodal PET/MRI segmentation is presented, considering volume…

Radiotherapy PlanningBrain tumorHealth Informatics02 engineering and technologyFuzzy C-means clusteringRadiosurgeryBrain tumorsMultimodal ImagingING-INF/05 - SISTEMI DI ELABORAZIONE DELLE INFORMAZIONI030218 nuclear medicine & medical imaging03 medical and health sciencesComputer-Assisted0302 clinical medicineRandom walker algorithm0202 electrical engineering electronic engineering information engineeringHumansMedicineSegmentationComputer visionRadiation treatment planningCluster analysisImage resolutionPET/MR imagingModality (human–computer interaction)Brain Neoplasmsbusiness.industryRadiotherapy Planning Computer-AssistedINF/01 - INFORMATICAMultimodal therapymedicine.diseaseRandom Walker algorithmMagnetic Resonance ImagingComputer Science ApplicationsBrain tumorGamma knife treatmentPositron-Emission Tomography020201 artificial intelligence & image processingMultimodal image segmentationBrain tumors; Fuzzy C-means clustering; Gamma knife treatments; Multimodal image segmentation; PET/MR imaging; Random Walker algorithm; Brain Neoplasms; Humans; Radiosurgery; Magnetic Resonance Imaging; Multimodal Imaging; Positron-Emission Tomography; Radiotherapy Planning Computer-AssistedArtificial intelligencebusinessGamma knife treatmentsSoftware
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Acrometastases to the Hand: A Systematic Review

2021

Background and Objectives: The term acrometastases (AM) refers to secondary lesions sited distally to the elbow and knee, representing 0.1% of all bony metastases. By frequency, pulmonary cancer and gastrointestinal and genitourinary tract neoplasms are the most responsible for the reported AM. Improvements in oncologic patient care favor an increase in the incidence of such rare cases. We performed a systematic review of acrometastases to the hand to provide further insight into the management of these fragile patients. We also present a peculiar case of simultaneous acrometastasis to the ring finger and pathological vertebral fracture. Material and Methods: A literature search according t…

AdultMaleMedicine (General)medicine.medical_specialtyLung NeoplasmsAdolescentmedicine.medical_treatmentBone NeoplasmsWristMetastasisFingersYoung AdultFinger PhalangesR5-920Breast cancerThumb metastasesmedicineCarcinomaChemotherapyHumansChildAgedAged 80 and overRadiotherapyAcrometastasesbusiness.industryGenitourinary systemIncidence (epidemiology)CarcinomaAcrometastases; Carcinoma; Chemotherapy; Immunotherapy; Radiotherapy; Thumb metastases; Adolescent; Adult; Aged; Aged 80 and over; Child; Female; Fingers; Humans; Male; Middle Aged; Prognosis; Young Adult; Bone Neoplasms; Finger Phalanges; Lung NeoplasmsGeneral MedicineMiddle AgedPrognosismedicine.diseasePrimary tumorRadiation therapymedicine.anatomical_structureFemaleSystematic ReviewImmunotherapyRadiologybusinessMedicina
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Biological target volume segmentation for radiotherapy treatment planning

2016

medicine.medical_specialtybusiness.industryBiophysicsGeneral Physics and Astronomy02 engineering and technologyGeneral MedicineRadiotherapy treatment planning021001 nanoscience & nanotechnologyBiological target0202 electrical engineering electronic engineering information engineeringMedicine020201 artificial intelligence & image processingRadiology Nuclear Medicine and imagingSegmentationRadiology0210 nano-technologybusinessVolume (compression)Physica Medica
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Robustness of PET Radiomics Features: Impact of Co-Registration with MRI

2021

Radiomics holds great promise in the field of cancer management. However, the clinical application of radiomics has been hampered by uncertainty about the robustness of the features extracted from the images. Previous studies have reported that radiomics features are sensitive to changes in voxel size resampling and interpolation, image perturbation, or slice thickness. This study aims to observe the variability of positron emission tomography (PET) radiomics features under the impact of co-registration with magnetic resonance imaging (MRI) using the difference percentage coefficient, and the Spearman’s correlation coefficient for three groups of images: (i) original PET, (ii) PET after co-…

TechnologyTomografía de emisión de positronesNeoplasias encefálicasCorrelation coefficientImagen por resonancia magnética:Phenomena and Processes::Mathematical Concepts::Probability::Uncertainty [Medical Subject Headings]QH301-705.5Computer scienceQC1-999:Diseases::Neoplasms::Neoplasms by Site::Nervous System Neoplasms::Central Nervous System Neoplasms::Brain Neoplasms [Medical Subject Headings]:Analytical Diagnostic and Therapeutic Techniques and Equipment::Diagnosis::Diagnostic Techniques and Procedures::Diagnostic Imaging::Magnetic Resonance Imaging [Medical Subject Headings]Co registrationFluid-attenuated inversion recovery:Organisms::Eukaryota::Animals::Chordata::Vertebrates::Mammals::Primates::Haplorhini::Catarrhini::Hominidae::Humans [Medical Subject Headings]Magnetic resonance imagingRadiomicsRobustness (computer science):Analytical Diagnostic and Therapeutic Techniques and Equipment::Diagnosis::Diagnostic Techniques and Procedures::Diagnostic Techniques Radioisotope::Radionuclide Imaging::Tomography Emission-Computed::Positron-Emission Tomography [Medical Subject Headings]Resamplingradiomics feature robustness; imaging quantification; [11C]-methionine positron emission tomography; PET/MRI co-registration Appl.medicineGeneral Materials ScienceBiology (General)QD1-999InstrumentationSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniFluid Flow and Transfer Processesmedicine.diagnostic_testbusiness.industryTPhysicsProcess Chemistry and TechnologyRadiomics feature robustnessGeneral EngineeringPET/MRI co-registrationMagnetic resonance imagingPattern recognitionEngineering (General). Civil engineering (General)Imaging quantificationComputer Science ApplicationsChemistry:Chemicals and Drugs::Amino Acids Peptides and Proteins::Amino Acids::Amino Acids Essential::Methionine [Medical Subject Headings]Positron emission tomography[11C]-methionine positron emission tomography:Analytical Diagnostic and Therapeutic Techniques and Equipment::Diagnosis::Prognosis [Medical Subject Headings]Artificial intelligenceTA1-2040businessApplied Sciences
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Clinical support in radiation therapy scenarios: MR brain tumor segmentation using an unsupervised fuzzy C-Means clustering technique

2016

medicine.medical_specialtyMR segmentationComputer sciencemedicine.medical_treatmentBiophysicsGeneral Physics and AstronomyFuzzy logicradiation therapy030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineClinical supportmedicineRadiology Nuclear Medicine and imagingCluster analysisSemi-automatic segmentationNeuro-radiosurgery treatmentbusiness.industryPattern recognitionGeneral MedicineFuzzy C-Means clusteringRadiation therapy030220 oncology & carcinogenesisArtificial intelligenceRadiologybusinessBrain tumor segmentationbrain tumorMR imaging
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Neuro-radiosurgery treatments: MRI brain tumor seeded image segmentation based on a cellular automata model

2016

Gross Tumor Volume (GTV) segmentation on medical images is an open issue in neuro-radiosurgery. Magnetic Resonance Imaging (MRI) is the most promi-nent modality in radiation therapy for soft-tissue anatomical districts. Gamma Knife stereotactic neuro-radiosurgery is a mini-invasive technique used to deal with inaccessible or insufficiently treated tumors. During the planning phase, the GTV is usually contoured by radiation oncologists using a manual segmentation procedure on MR images. This methodology is certainly time-consuming and op-erator-dependent. Delineation result repeatability, in terms of both intra- and inter-operator reliability, is only obtained by using computer-assisted appr…

medicine.medical_specialtyComputer sciencemedicine.medical_treatment02 engineering and technologyCellular AutomataBrain tumors; Cellular automata; Gamma knife treatments; MR imaging; Semi-automatic segmentationBrain tumorsRadiosurgery030218 nuclear medicine & medical imagingTheoretical Computer Science03 medical and health sciences0302 clinical medicineGamma Knife treatments0202 electrical engineering electronic engineering information engineeringmedicineSegmentationMri brainModality (human–computer interaction)medicine.diagnostic_testSemi-automatic segmentationbusiness.industryINF/01 - INFORMATICAMagnetic resonance imagingImage segmentationCellular automatonRadiation therapyBrain tumor020201 artificial intelligence & image processingGamma Knife treatmentArtificial intelligenceRadiologybusinessMR imaging
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Using anatomic and metabolic imaging in stereotactic radio neuro-surgery treatments

2016

PET/MR imagingmedicine.medical_specialtyNeuro-radiosurgerybusiness.industryMetabolic imagingBiophysicsGeneral Physics and AstronomyGeneral MedicineRandom Walker algorithmFuzzy C-Means clustering030218 nuclear medicine & medical imagingBrain tumor03 medical and health sciences0302 clinical medicineRandom walker algorithm030220 oncology & carcinogenesismedicineRadiology Nuclear Medicine and imagingNeurosurgeryRadiologyPet mr imagingbusinessNuclear medicine
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Active contour algorithm with discriminant analysis for delineating tumors in positron emission tomography.

2019

Abstract In the context of cancer delineation using positron emission tomography datasets, we present an innovative approach which purpose is to tackle the real-time, three-dimensional segmentation task in a full, or at least nearly full automatized way. The approach comprises a preliminary initialization phase where the user highlights a region of interest around the cancer on just one slice of the tomographic dataset. The algorithm takes care of identifying an optimal and user-independent region of interest around the anomalous tissue and located on the slice containing the highest standardized uptake value so to start the successive segmentation task. The three-dimensional volume is then…

Positron emission tomographyComputer scienceInitializationMedicine (miscellaneous)Context (language use)Imaging phantomActive contour algorithm03 medical and health sciences0302 clinical medicineRegion of interestArtificial IntelligenceNeoplasmsmedicineHumansSegmentation030304 developmental biologyRetrospective Studies0303 health sciencesActive contour modelDiscriminant analysimedicine.diagnostic_testbusiness.industryDiscriminant AnalysisPattern recognitionLinear discriminant analysisPositron emission tomographyBiological target volume segmentationPositron-Emission TomographyArtificial intelligencebusiness030217 neurology & neurosurgeryAlgorithmsArtificial intelligence in medicine
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Metabolic Response Assessment in Non-Small Cell Lung Cancer Patients after Platinum-Based Therapy: A Preliminary Analysis

2015

The purpose of this study was to evaluate the clinical value of PET (Positron Emission Tomography) for early prediction of tumor response to platinum-based therapy in patients with nonsmall cell lung cancer (NSCLC). The evaluation was carried out comparing the standard treatment response using RECIST (Response Evaluation Criteria in Solid Tumors) with metabolic treatment response according to European Organization for Research and Treatment of Cancer (EORTC) recommendations, PET Response Criteria in Solid Tumors (PERCIST), Total Lesion Glycolysis (TLG) and Metabolic Tumor Volume (MTV). Seventeen inoperable patients with stage IV NSCLC were enrolled between October 2011 and June 2013: PET st…

Oncologymedicine.medical_specialtybusiness.industryF-FDG PETmedicine.disease18 F-FDG PET EORTC Non-small cell lung cancer PERCIST RECIST Therapy MonitoringPreliminary analysisResponse assessmentEORTCNon-small cell lung cancerRECISTTherapy MonitoringInternal medicinemedicineF-18-FDG PETRadiology Nuclear Medicine and imagingTherapy monitoringRadiologyNon small cellLung cancerbusinessPERCIST
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A Graph-Based Method for PET Image Segmentation in Radiotherapy Planning: A Pilot Study

2013

Target volume delineation of Positron Emission Tomography (PET) images in radiation treatment planning is challenging because of the low spatial resolution and high noise level in PET data. The aim of this work is the devel- opment of an accurate and fast method for semi-automatic segmentation of me- tabolic regions on PET images. For this purpose, an algorithm for the biological tumor volume delineation based on random walks on graphs has been used. Va- lidation was first performed on phantoms containing spheres and irregular in- serts of different and known volumes, then tumors from a patient with head and neck cancer were segmented to discuss the clinical applicability of this algo- rith…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionimedicine.diagnostic_testRadiotherapybusiness.industryComputer sciencemedicine.medical_treatmentGraph basedHead and Neck cancerImage segmentationGraphGraphRadiation therapySegmentationPETPositron emission tomographymedicineSegmentationComputer visionSegmentation Graph PET Head and Neck cancer RadiotherapyArtificial intelligenceRadiation treatment planningbusinessImage resolution
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A preliminary PET radiomics study of brain metastases using a fully automatic segmentation method

2020

AbstractBackgroundPositron Emission Tomography (PET) is increasingly utilized in radiomics studies for treatment evaluation purposes. Nevertheless, lesion volume identification in PET images is a critical and still challenging step in the process of radiomics, due to the low spatial resolution and high noise level of PET images. Currently, the biological target volume (BTV) is manually contoured by nuclear physicians, with a time expensive and operator-dependent procedure.This study aims to obtain BTVs from cerebral metastases in patients who underwent L-[11C]methionine (11C-MET) PET, using a fully automatic procedure and to use these BTVs to extract radiomics features to stratify between p…

MalePositron emission tomographyComputer scienceLesion volumelcsh:Computer applications to medicine. Medical informaticsBiochemistry030218 nuclear medicine & medical imagingLesion03 medical and health sciences0302 clinical medicineRadiomicsStructural BiologyArtificial IntelligencemedicineHumansSegmentationNeoplasm Metastasislcsh:QH301-705.5Molecular BiologyCancerActive contour modelRadiomicsmedicine.diagnostic_testBrain Neoplasmsbusiness.industryApplied MathematicsResearchCancerPattern recognitionMiddle AgedPrognosismedicine.diseaseComputer Science ApplicationsCancer treatmentBiological target volumelcsh:Biology (General)Positron emission tomographyFeature (computer vision)030220 oncology & carcinogenesisPositron-Emission TomographyFully automaticlcsh:R858-859.7FemaleActive contourArtificial intelligencemedicine.symptomRadiomicActive contour; Biological target volume; Cancer; Positron emission tomography; Radiomics.businessBMC Bioinformatics
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An automatic method for metabolic evaluation of gamma knife treatments

2015

Lesion volume delineation of Positron Emission Tomography images is challenging because of the low spatial resolution and high noise level. Aim of this work is the development of an operator independent segmentation method of metabolic images. For this purpose, an algorithm for the biological tumor volume delineation based on random walks on graphs has been used. Twenty-four cerebral tumors are segmented to evaluate the functional follow-up after Gamma Knife radiotherapy treatment. Experimental results show that the segmentation algorithm is accurate and has real-time performance. In addition, it can reflect metabolic changes useful to evaluate radiotherapy response in treated patients.

medicine.diagnostic_testComputer sciencebusiness.industrymedicine.medical_treatmentComputer Science (all)PET imagingPattern recognitionLesion volumeRandom walkGamma knifeTheoretical Computer ScienceRadiation therapyBiological target volumeSegmentationBiological target volume Gamma Knife treatment PET imaging Random walk SegmentationPositron emission tomographymedicineSegmentationRadiotherapy treatmentGamma Knife treatmentArtificial intelligenceNoise levelbusinessImage resolution
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253. An accurate and operator independent method for biological tumour volume segmentation

2018

Purpose The aim of this paper is to develop an operator independent method for biological tumour volume (BTV) delineation from Positron Emission Tomography (PET) images. BTV delineation is challenging because of the low spatial resolution and high noise level in PET images. In addition, BTV varies substantially depending on the method used to segment. Manual delineation is widely-used, but it is strongly user dependent. Methods The proposed method starts with the automatic identification of the PET slice with maximum Standardized Uptake Value (SUV). Then, a user- independent mask is obtained by a rough pre-segmentation step and it is used to perform the local active contour segmentation on …

Active contour modelSimilarity (geometry)medicine.diagnostic_testComputer sciencebusiness.industryBiophysicsGeneral Physics and AstronomyContext (language use)Pattern recognitionStandardized uptake valueGeneral MedicineImaging phantomPositron emission tomographymedicineRadiology Nuclear Medicine and imagingSegmentationArtificial intelligencebusinessImage resolutionPhysica Medica
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68 ga-dotatoc pet/ct follow up after single or hypofractionated gamma knife icon radiosurgery for meningioma patients

2021

68Ga-DOTATOC represents a useful tool in tumor contouring for radiosurgery planning. We present a case series of patients affected by meningiomas on who we performed 68Ga-DOTATOC positron emission tomography (PET)/CT pre-operatively, a subgroup of which also underwent a post-operative 68Ga-DOTATOC PET/CT to evaluate the standardized uptake value (SUV) modification after Gamma Knife ICON treatment in single or hypofractionated fractions. Twenty patients were enrolled/included in this study: ten females and ten males. The median age was 52 years (range 33–80). The median tumor diameter was 3.68 cm (range 0.12–22.26 cm), and the median pre-radiotherapy maximum SUV value was 11 (range 2.3–92). …

medicine.medical_treatmentStandardized uptake valueGalliumGamma knifeRadiosurgeryRadiosurgeryArticlelcsh:RC321-57168ga dotatocMeningioma03 medical and health sciences<sup>68</sup>Ga-DOTATOC PET/CT0302 clinical medicinemedicinelcsh:Neurosciences. Biological psychiatry. NeuropsychiatryPET-CTContouringmedicine.diagnostic_testbusiness.industryGamma KnifeGeneral NeuroscienceFollow upmedicine.diseasePositron emission tomography030220 oncology & carcinogenesisNuclear medicinebusiness68Ga-DOTATOC PET/CTMeningiomaHypofractionated030217 neurology & neurosurgery
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Analysis of Metabolic Parameters Coming from Basal and Interim PET in Hodgkin Lymphoma

2018

Objective: Positron Emission Tomography (PET) with F-18-Fluoro-deoxy-glucose (FDG) emerged as a prognostic tool to predict treatment outcome in Hodgkin Lymphoma (HL). Moreover, a FDG-PET adapted strategy is currently assessed in clinical trial to minimize the toxic effect while maintaining the efficacy of treatment in HL. Purpose was to analyze the quantitative parameters to support the prognostic role of FDG-PET today based on the semi-quantitative Deauville 5-point Scale (D5-PS). Methods: This retrospective study included 53 patients diagnosed with advanced-stage HL between 2009 and 2014, enrolled in the PET response-adapted clinical trial HD 0607. FDG-PET was performed at baseline (PET0)…

Pathologymedicine.medical_specialtyChemothrapy; FDG PET; Hodgkin lymphoma; Metabolic parameters; Metabolic tumor volume; Prognostic value; Radiology Nuclear Medicine and Imagingbusiness.industryHODGkin lymphomaMetabolic tumor volume02 engineering and technology021001 nanoscience & nanotechnologyInterim pet03 medical and health sciencesBasal (phylogenetics)0302 clinical medicineNuclear Medicine and ImagingFDG PETmedicineHodgkin lymphomaRadiology Nuclear Medicine and imaging030212 general & internal medicineMetabolic parametersRadiology0210 nano-technologyNuclear medicinebusinessPrognostic valueChemothrapyCurrent Medical Imaging Reviews
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