Computer-aided prognosis: predicting patient and disease outcome via quantitative fusion of multi-scale, multi-modal data.
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Digital Pathology: Data-Intensive Frontier in Medical Imaging: Health-information sharing, specifically of digital pathology, is the subject of this paper which discusses how sharing the rich images in pathology can stretch the capabilities of all oPredicting classifier performance with limited training data: applications to computer-aided diagnosis in breast and prostate cancer.Adaptive Dimensionality Reduction with Semi-Supervision (AdDReSS): Classifying Multi-Attribute Biomedical Data.A methodology to ensure and improve accuracy of Ki67 labelling index estimation by automated digital image analysis in breast cancer tissueEmerging Tools for Computer-Aided Diagnosis and Prognostication.Supervised regularized canonical correlation analysis: integrating histologic and proteomic measurements for predicting biochemical recurrence following prostate surgeryImmunohistochemistry profiles of breast ductal carcinoma: factor analysis of digital image analysis data.Automated quantification of aligned collagen for human breast carcinoma prognosis.An Efficient Computational Framework for the Analysis of Whole Slide Images: Application to Follicular Lymphoma ImmunohistochemistryNear-infrared fluorescent digital pathology for the automation of disease diagnosis and biomarker assessment.Identifying MRI markers associated with early response following laser ablation for neurological disorders: preliminary findings.Integrated morphologic analysis for the identification and characterization of disease subtypes.Content-based image retrieval of digitized histopathology in boosted spectrally embedded spaces.GUDM: Automatic Generation of Unified Datasets for Learning and Reasoning in HealthcareDimensionality reduction-based fusion approaches for imaging and non-imaging biomedical data: concepts, workflow, and use-cases.Detection of Phenotypic Alterations Using High-Content Analysis of Whole-Slide ImagesOut-of-Sample Extrapolation utilizing Semi-Supervised Manifold Learning (OSE-SSL): Content Based Image Retrieval for Histopathology ImagesExplicit shape descriptors: novel morphologic features for histopathology classification.Multi-Pass Adaptive Voting for Nuclei Detection in Histopathological Images.Nuclear morphometry, nucleomics and prostate cancer progressionPathology to enhance precision medicine in oncology: lessons from landscape ecologyCascaded Multi-view Canonical Correlation (CaMCCo) for Early Diagnosis of Alzheimer's Disease via Fusion of Clinical, Imaging and Omic Features.Quantitative modeling of clinical, cellular, and extracellular matrix variables suggest prognostic indicators in cancer: a model in neuroblastoma.Evaluating stability of histomorphometric features across scanner and staining variations: prostate cancer diagnosis from whole slide images.Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear features from digital H&E images.Interactive phenotyping of large-scale histology imaging data with HistomicsML.Digital immunohistochemistry: new horizons and practical solutions in breast cancer pathology.PET and MRI image fusion based on combination of 2-D Hilbert transform and IHS method.Medical Image Retrieval Using Multi-Texton Assignment.Biomedical informatics for computer-aided decision support systems: a survey.Digital liver biopsy: Bio-imaging of fatty liver for translational and clinical research.A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue.Translational informatics in personalized medicineStable and discriminating features are predictive of cancer presence and Gleason grade in radical prostatectomy specimens: a multi-site study
P2860
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P2860
Computer-aided prognosis: predicting patient and disease outcome via quantitative fusion of multi-scale, multi-modal data.
description
2011 nî lūn-bûn
@nan
2011 թուականի Փետրուարին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի փետրվարին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
Computer-aided prognosis: pred ...... multi-scale, multi-modal data.
@ast
Computer-aided prognosis: pred ...... multi-scale, multi-modal data.
@en
type
label
Computer-aided prognosis: pred ...... multi-scale, multi-modal data.
@ast
Computer-aided prognosis: pred ...... multi-scale, multi-modal data.
@en
prefLabel
Computer-aided prognosis: pred ...... multi-scale, multi-modal data.
@ast
Computer-aided prognosis: pred ...... multi-scale, multi-modal data.
@en
P2093
P1476
Computer-aided prognosis: pred ...... multi-scale, multi-modal data.
@en
P2093
Ajay Basavanhally
George Lee
Scott Doyle
Shannon Agner
P304
P356
10.1016/J.COMPMEDIMAG.2011.01.008
P577
2011-02-17T00:00:00Z