Carta Revisado por pares

Journey toward Computer-aided Diagnosis: Role of Image Texture Analysis

1999; Radiological Society of North America; Volume: 213; Issue: 2 Linguagem: Inglês

10.1148/radiology.213.2.r99nv49317

ISSN

1527-1315

Autores

Georgia D. Tourassi,

Tópico(s)

Breast Lesions and Carcinomas

Resumo

HomeRadiologyVol. 213, No. 2 PreviousNext EditorialJourney toward Computer-aided Diagnosis: Role of Image Texture AnalysisGeorgia D. TourassiGeorgia D. TourassiAuthor Affiliations1From the Department of Radiology, Duke University Medical Center, Box 3302, Erwin Rd, Durham, NC 27710. Received July 6, 1999; accepted July 16. Address reprint requests to the author (e-mail: gt@deckard .mc.duke.edu).Georgia D. TourassiPublished Online:Nov 1 1999https://doi.org/10.1148/radiology.213.2.r99nv49317MoreSectionsFull textPDF ToolsAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookXLinked In References 1 Chen DR, Chang RF, Huang YL. Computer-aided diagnosis applied to US of solid breast nodules by using neural networks. Radiology 1999; 213:407-412. Link, Google Scholar2 Jackson VP. Management of solid breast nodules: what is the role of sonography? (editorial). Radiology 1995; 196:14-15. Link, Google Scholar3 Morishita J, Doi K, Katsuragawa S, Monnier-Cholley L, MacMahon H. Computer-aided diagnosis for interstitial infiltrates in chest radiographs: optical-density dependence of texture measures. Med Phys 1995; 22:1515-1522. Crossref, Medline, Google Scholar4 Vittitoe NF, Baker JA, Floyd CE, Jr. Fractal texture analysis in computer-aided diagnosis of solitary pulmonary nodules. Acad Radiol 1997; 4:96-101. Crossref, Medline, Google Scholar5 Wei D, Chan HP, Helvie MA, et al. Classification of mass and normal breast tissue on digital mammograms: multiresolution texture analysis. Med Phys 1995; 22:1501-1513. Crossref, Medline, Google Scholar6 Chan HP, Sahiner B, Petrick N, et al. Computerized classification of malignant and benign microcalcifications on mammograms: texture analysis using an artificial neural network. Phys Med Biol 1997; 42:549-567. Crossref, Medline, Google Scholar7 Petrick N, Chan HP, Wei D, Sahiner B, Helvie MA, Adler DD. Automated detection of breast masses on mammograms using adaptive contrast enhancement and texture classification. Med Phys 1996; 23:1685-1696. Crossref, Medline, Google Scholar8 McPherson DD, Aylward PE, Knosp BM, et al. Ultrasound characterization of acute myocardial ischemia by quantitative texture analysis. Ultrason Imaging 1986; 8:227-240. Crossref, Medline, Google Scholar9 Ito M, Ohki M, Hayashi K, Yamada M, Uetani M, Nakamura T. Trabecular texture analysis of CT images in the relationship with spinal fracture. Radiology 1995; 194:55-59. Link, Google Scholar10 Staff RT, Gemmell HG, Duff PM, et al. Decompression illness in sports divers detected with technetium-99m-HMPAO SPECT and texture analysis. J Nucl Med 1996; 37:1154-1158. Medline, Google Scholar11 Lucht R, Brix G, Lorenz WJ. Texture analysis of differently reconstructed PET images. Phys Med Biol 1996; 41:2207-2219. Crossref, Medline, Google Scholar12 Kjaer L, Ring P, Thomsen C, Henriksen O. Texture analysis in quantitative MR imaging: tissue characterisation of normal brain and intracranial tumours at 1.5 T. Acta Radiol 1995; 36:127-135. Crossref, Medline, Google Scholar13 Robinson PJ. Radiology's Achilles' heel: error and variation in the interpretation of the Roentgen image. Br J Radiol 1997; 70:1085-1098. Crossref, Medline, Google Scholar14 Anderson RE, Hill RB, Key CR. The sensitivity and specificity of clinical diagnostics during five decades: toward an understanding of necessary fallibility. JAMA 1989; 261:1610-1617. Crossref, Medline, Google Scholar15 Renfrew DL, Franken EA, Jr, Berbaum KS, Weigelt FH, Abu-Yousef MM. Error in radiology: classification and lessons in 182 cases presented at a problem case conference. Radiology 1992; 183:145-150. Link, Google Scholar16 Brady AP, Stevenson GW, Stevenson I. Colorectal cancer overlooked at barium enema examination and colonoscopy: continuing perceptual problem. Radiology 1994; 192:373-378. Link, Google Scholar17 Berlin L. Malpractice issues in radiology: perceptual errors. AJR 1996; 167:587-590. Crossref, Medline, Google Scholar18 Berlin L, Hendrix RW. Malpractice issues in radiology: perceptual errors and negligence. AJR 1998; 170:863-867. Crossref, Medline, Google Scholar19 Berlin L. Errors in judgment. AJR 1996; 166:1259-1261. Crossref, Medline, Google Scholar20 Durgin FH, Proffitt DR. Visual learning in the perception of texture: simple and contingent aftereffects of texture density. Spat Vis 1996; 9:424-474. Google Scholar21 Folfiak P. Forming sparse representations by local anti-Hebbian learning. Biol Cybern 1990; 64:165-170. Crossref, Medline, Google Scholar22 Field DJ, Hayes A, Hess RF. Contour integration by the human visual system: evidence for a local "association field". Vision Res 1993; 33:173-193. Crossref, Medline, Google Scholar23 Karni A, Sagi D. The time course of learning a visual skill. Nature 1993; 365:250-252. Crossref, Medline, Google Scholar24 Tuceryan M, Jain AK. Texture analysis. In: Chen C, Pau L, Wang P, eds. Handbook of pattern recognition and computer vision. River Edge, NJ: World Scientific, 1993; 235-276. Crossref, Google Scholar25 Julesz B, Gilbert EN, Shepp LA, Frish HL. Inability of humans to discriminate between visual features that agree in second-order statistics—revisited. Perception 1973; 2:391-405. Crossref, Medline, Google Scholar26 Julesz B. Visual discrimination of textures with identical third-order statistics. Biol Cybern 1978; 31:137-140. Crossref, Medline, Google Scholar27 Harlow CA, Eisenbeis SA. The analysis of radiographic images. IEEE Trans Comput 1973; C22:678-689. Google Scholar28 Egglin TK, Feinstein AR. Context bias: a problem in diagnostic radiology. JAMA 1996; 276:1752-1755. Crossref, Medline, Google Scholar29 Scott JA, Fisher RE, Palmer EL. Neural networks in ventilation-perfusion imaging. II. Effects of interpretive variability. Radiology 1996; 198:707-713. Google Scholar30 Baker JA, Kornguth PJ, Soo MS, Walsh R, Mengoni P. Sonography of solid breast lesions: observer variability of lesion description and assessment. AJR 1999; 172:1621-1625. Crossref, Medline, Google Scholar31 Stavros AT, Thickman D, Rapp CL, Dennis MA, Parker SH, Sisney GA. Solid breast nodules: use of sonography to distinguish between benign and malignant lesions. Radiology 1995; 196:123-134. Link, Google Scholar32 Huisman HJ, Thijssen JM. Adaptive texture feature extraction with application to ultrasonic image analysis. Ultrason Imaging 1998; 20:132-148. Crossref, Medline, Google Scholar33 Kegelmeyer WP, Jr, Pruneda JM, Bourland PD, Hillis AH, Riggs MW, Nipper ML. Computer-aided mammographic screening for spiculated lesions. Radiology 1994; 191:315-317. Link, Google Scholar34 Jiang YL, Nishikawa RM, Schmidt RA, Metz CE, Giger ML, Doi K. Improving breast cancer diagnosis with computer-aided diagnosis. Acad Radiol 1999; 6:22-33. Crossref, Medline, Google ScholarArticle HistoryPublished in print: Nov 1999 FiguresReferencesRelatedDetailsCited ByThe role of radiomics in computed tomography, magnetic resonance imaging, and ultrasound for renal tumors' diagnoses: A systematic reviewZenghuiXi, JingLi, XueLiu, XiumeiGao, YaweiChen2024Mar1 | Journal of Radiation Research and Applied Sciences, Vol. 17, No. 1CCL18, CHI3L1, ANG2, IL-6 systemic levels are associated with the extent of lung damage and radiomic features in SARS-CoV-2 infectionIlariaFerrigno, LauraVerzellesi, MartaOttone, MartinaBonacini, AlessandroRossi, GiuliaBesutti, EfremBonelli, RossanaColla, NicolaFacciolongo, ElisabettaTeopompi, MarcoMassari, PamelaMancuso, Anna MariaFerrari, PierpaoloPattacini, ValeriaTrojani, MarcoBertolini, AndreaBotti, AlessandroZerbini, PaoloGiorgi Rossi, MauroIori, CarloSalvarani, StefaniaCroci3 February 2024 | Inflammation Research, Vol. 29When Sex Matters: Differences in the Central Nervous System as Imaged by OCT through the RetinaAnaNunes, PedroSerranho, PedroGuimarães, JoãoFerreira, MiguelCastelo-Branco, RuiBernardes25 December 2023 | Journal of Imaging, Vol. 10, No. 1Improved Cervical Lymph Node Characterization among Patients with Head and Neck Squamous Cell Carcinoma Using MR Texture Analysis Compared to Traditional FDG-PET/MR Features AloneEric K.van Staalduinen, RobertMatthews, AdamKhan, IshaPunn, Renee F.Cattell, HaifangLi, AnaFranceschi, Ghassan J.Samara, LukaszCzerwonka, LevBangiyev, Tim Q.Duong28 December 2023 | Diagnostics, Vol. 14, No. 1CT Texture Analysis in Nonalcoholic Fatty Liver Disease (NAFLD)Laura E.Dichtel, AzadehTabari, Nathaniel D.Mercaldo, Kathleen E.Corey, JadHusseini, Stephanie A.Osganian, Mark L.Chicote, Elizabeth M.Rao, Karen K.Miller, Miriam A.Bredella2023Sep1 | Journal of Clinical and Experimental Hepatology, Vol. 13, No. 5Performance of radiomics-based artificial intelligence systems in the diagnosis and prediction of treatment response and survival in esophageal cancer: a systematic review and meta-analysis of diagnostic accuracyNainikaMenon, NadiaGuidozzi, SwathikanChidambaram, Sheraz RehanMarkar26 May 2023 | Diseases of the Esophagus, Vol. 36, No. 6Artificial intelligence in coronary computed tomography angiography: Demands and solutions from a clinical perspectiveBettinaBaeßler, MichaelGötz, CharalambosAntoniades, Julius F.Heidenreich, TimLeiner, MeinradBeer2023 | Frontiers in Cardiovascular Medicine, Vol. 10Feature selection algorithm based on binary BAT algorithm and optimum path forest classifier for breast cancer detection using both echographic and elastographic mode ultrasound imagesSSasikala, MEzhilarasi, SArunkumar2023 | Journal of Cancer Research and Therapeutics, Vol. 19, No. 2Radiomics applications in cardiac imaging: a comprehensive reviewTizianoPolidori, DomenicoDe Santis, CarlottaRucci, GiuseppeTremamunno, GiuliaPiccinni, LucaPugliese, MartaZerunian, GisellaGuido, FrancescoPucciarelli, BenedettaBracci, MichelaPolici, AndreaLaghi, DamianoCaruso2023 | La radiologia medica, Vol. 128, No. 8Artificial Intelligence-Assisted Processing of Anterior Segment OCT Images in the Diagnosis of Vitreoretinal LymphomaFabrizioGozzi, MarcoBertolini, PietroGentile, LauraVerzellesi, ValeriaTrojani, LucaDe Simone, ElenaBolletta, ValentinaMastrofilippo, EnricoFarnetti, DavideNicoli, StefaniaCroci, LuciaBelloni, AlessandroZerbini, ChantalAdani, MicheleDe Maria, AretiKosmarikou, MarcoVecchi, AlessandroInvernizzi, FiorellaIlariucci, MagdaZanelli, MauroIori, LucaCimino2023 | Diagnostics, Vol. 13, No. 14Prognostic Values of Primary Tumor Textural Heterogeneity and Blood Biomarkers in High-risk NeuroblastomaOzgeVural, UgurayAydos, ArzuOkur, Faruk GüçlüPinarli, Lütfiye ÖzlemAtay16 March 2023 | Journal of Pediatric Hematology/Oncology, Vol. Publish Ahead of PrintRadiomics and Texture AnalysisAdarshGhosh, Suraj D.Serai18 November 2023Prognostic value of fluorodeoxyglucose positron emission tomography derived metabolic parameters and textural features in pediatric sarcomaUğurayAydos, TayyibeSever, ÖzgeVural, BüşraTopuz Türkcan, ArzuOkur, Ümit ÖzgürAkdemir, AylarPoyraz, Faruk GüçlüPinarli, Lütfiye ÖzlemAtay, CeydaKaradeniz4 May 2022 | Nuclear Medicine Communications, Vol. 43, No. 7Texture Analysis of Magnetic Resonance Images Enables Phenotyping of Potentially Painful Annular FissuresStefanieEriksson, ChristianWaldenberg, LeifTorén, AnnaGrimby-Ekman, HelenaBrisby, HannaHebelka, KerstinLagerstrand7 July 2021 | Spine, Vol. 47, No. 5Contemporary Medical ImagingBettinaBaessler2022Medical RadiologyBettinaBaessler, DavideCester2022Gradient contouring and texture modelling based CAD system for improved TB classificationJ.Rajeswari, J.Raja, S.Jayashri2022 | Automated Software Engineering, Vol. 29, No. 1Artificial Intelligence and Cardiovascular Magnetic Resonance Imaging in Myocardial Infarction PatientsJun HuaChong, MusaAbdulkareem, Steffen E.Petersen, Mohammed Y.Khanji2022 | Current Problems in Cardiology, Vol. 47, No. 12Diagnosis and Treatment of Acromegaly: An UpdateNazaninErshadinia, Nicholas A.Tritos2022 | Mayo Clinic Proceedings, Vol. 97, No. 2Development and validation of a novel model incorporating MRI-based radiomics signature with clinical biomarkers for distinguishing pancreatic carcinoma from mass-forming chronic pancreatitisJingjingLiu, LeiHu, BiZhou, ChungenWu, YingshengCheng2022 | Translational Oncology, Vol. 18Radiomics and machine learning for the diagnosis of pediatric cervical non-tuberculous mycobacterial lymphadenitisYarabAl Bulushi, ChristineSaint-Martin, NikeshMuthukrishnan, FarhadMaleki, CarolineReinhold, RezaForghani2022 | Scientific Reports, Vol. 12, No. 1Radiomics as an emerging tool in the management of brain metastasesAlexanderNowakowski, ZubinLahijanian, ValeriePanet-Raymond, Peter MSiegel, KevinPetrecca, FarhadMaleki, MatthewDankner2022 | Neuro-Oncology Advances, Vol. 4, No. 1A review on advances in 18F-FDG PET/CT radiomics standardisation and application in lung disease managementNoushinAnan, RafidahZainon, MahbubunnabiTamal2022 | Insights into Imaging, Vol. 13, No. 1Novel Harmonization Method for Multi-Centric Radiomic Studies in Non-Small Cell Lung CancerMarcoBertolini, ValeriaTrojani, AndreaBotti, NoemiCucurachi, MarcoGalaverni, SalvatoreCozzi, PaoloBorghetti, SalvatoreLa Mattina, EdoardoPastorello, MicheleAvanzo, AlbertoRevelant, MatteoSepulcri, ChiaraParonetto, StefanoUrsino, GiuliaMalfatti, NiccolòGiaj-Levra, LorenzoFalcinelli, CinziaIotti, MauroIori, PatriziaCiammella2022 | Current Oncology, Vol. 29, No. 8The Applications of Artificial Intelligence in Cardiovascular Magnetic Resonance—A Comprehensive ReviewAdrianaArgentiero, GiuseppeMuscogiuri, Mark G.Rabbat, ChiaraMartini, NicolòSoldato, PaoloBasile, AndreaBaggiano, SaimaMushtaq, LauraFusini, Maria ElisabettaMancini, NicolaGaibazzi, Vincenzo EzioSantobuono, SandroSironi, GianlucaPontone, Andrea IgorenGuaricci2022 | Journal of Clinical Medicine, Vol. 11, No. 10Radiomics in Urolithiasis: Systematic Review of Current Applications, Limitations, and Future DirectionsEe JeanLim, DanieleCastellani, Wei ZhengSo, Khi YungFong, Jing QiuLi, Ho YeeTiong, NarimanGadzhiev, Chin TiongHeng, Jeremy Yuen-ChunTeoh, NitheshNaik, KhurshidGhani, KemalSarica, JeanDe La Rosette, BhaskarSomani, VineetGauhar2022 | Journal of Clinical Medicine, Vol. 11, No. 17A Review of Radiomics and Artificial Intelligence and Their Application in Veterinary Diagnostic ImagingOthmaneBouhali, HalimaBensmail, AliSheharyar, FlorentDavid, Jessica P.Johnson2022 | Veterinary Sciences, Vol. 9, No. 11Association Between Histopathology and Magnetic Resonance Imaging Texture in Grading Gliomas Based on Intraoperative Magnetic Resonance Navigated Stereotactic BiopsyWentingRui, HaopengPang, QianXie, YinWang, ShaofengDuan, YanRen, ZhenweiYao4 August 2021 | Journal of Computer Assisted Tomography, Vol. 45, No. 5Características de textura del tumor primario en imágenes de 18F-FDG PET en cáncer de pulmón de células no pequeñas: la relación entre parámetros de imágenes y parámetros histopatológicosU.Aydos, E.R.Ünal, M.Özçelik, D.Akdemir, Ö.Ekinci, A.İ.Taştepe, L.Memiş, L.Ö.Atay, Ü.Ö.Akdemir2021 | Revista Española de Medicina Nuclear e Imagen Molecular, Vol. 40, No. 6Texture features of primary tumor on 18F-FDG PET images in non-small cell lung cancer: The relationship between imaging and histopathological parametersUğurayAydos, Emel RodopluÜnal, MahsunÖzçelik, DenizAkdemir, ÖzgürEkinci, Abdullah İrfanTaştepe, LeylaMemiş, Lütfiye ÖzlemAtay, Ümit ÖzgürAkdemir2021 | Revista Española de Medicina Nuclear e Imagen Molecular (English Edition), Vol. 40, No. 6Multifractal analysis of glaciers in the Lombardy region of the Italian AlpsMarinaCarpineti, AndreaRossoni, AntonellaSenese, DavideMaragno, Guglielmina ADiolaiuti, AlbertoVailati2021 | Journal of Physics: Complexity, Vol. 2, No. 2Decoding intra-tumoral spatial heterogeneity on radiological images using the Hilbert curveLuWang, NanXu, JiangdianSong2021 | Insights into Imaging, Vol. 12, No. 1Radiomics Model Based on MR Images to Discriminate Pancreatic Ductal Adenocarcinoma and Mass-Forming Chronic Pancreatitis LesionsYanDeng, BingMing, TingZhou, Jia-longWu, YongChen, PeiLiu, JuZhang, Shi-yongZhang, Tian-wuChen, Xiao-MingZhang2021 | Frontiers in Oncology, Vol. 11CT Texture Analysis for Differentiating Bronchiolar Adenoma, Adenocarcinoma In Situ, and Minimally Invasive Adenocarcinoma of the LungJinjuSun, KaijunLiu, HaipengTong, HuanLiu, XiaoguangLi, YiLuo, YangLi, YunYao, RongbingJin, JingqinFang, XiaoChen2021 | Frontiers in Oncology, Vol. 11Radiomics in Renal Cell Carcinoma—A Systematic Review and Meta-AnalysisJuliaMühlbauer, LuisaEgen, Karl-FriedrichKowalewski, MaurizioGrilli, Margarete T.Walach, NiklasWesthoff, PhilippNuhn, Fabian C.Laqua, BettinaBaessler, Maximilian C.Kriegmair2021 | Cancers, Vol. 13, No. 6Evaluation of 68Ga-PSMA-11 PET-MRI in Patients with Advanced Prostate Cancer Receiving 177Lu-PSMA-617 Therapy: A Radiomics AnalysisWolfgangRoll, PhilippSchindler, MaxMasthoff, RobertSeifert, KatrinSchlack, MartinBögemann, LarsStegger, MatthiasWeckesser, KambizRahbar2021 | Cancers, Vol. 13, No. 15FAST INTERACTIVE REGIONAL PATTERN MERGING FOR GENERIC TISSUE SEGMENTATION IN HISTOPATHOLOGY IMAGESKuo-LungLor, Chung-MingChen2021 | Biomedical Engineering: Applications, Basis and Communications, Vol. 33, No. 02Whole-lesion ADC histogram analysis versus single-slice ADC measurement for the differentiation of benign and malignant soft tissue tumorsMesutOzturk, Ahmet VeyselPolat, Mustafa BekirSelcuk2021 | European Journal of Radiology, Vol. 143HCC advances in diagnosis and prognosis: Digital and ImagingRiccardoSartoris, JulesGregory, MarcoDioguardi Burgio, MaximeRonot, ValérieVilgrain2021 | Liver International, Vol. 41, No. S1Precision Digital Oncology: Emerging Role of Radiomics-based Biomarkers and Artificial Intelligence for Advanced Imaging and Characterization of Brain TumorsReza Forghani, 31 July 2020 | Radiology: Imaging Cancer, Vol. 2, No. 4Communications in Computer and Information ScienceAbdullahAlfahaid, TimMorris, TimCootes, Pearse A.Keane, HagarKhalid, NikolasPontikos, PanagiotisSergouniotis, KonstantinosBalaskas2020 | , Vol. 1065Springer Tracts in Nature-Inspired ComputingS.Sasikala, M.Ezhilarasi, S.Arun Kumar2020MRI texture analysis in acromegaly and its role in predicting response to somatostatin receptor ligandsBrandon P.Galm, ColleenBuckless, BrookeSwearingen, MartinTorriani, AnneKlibanski, Miriam A.Bredella, Nicholas A.Tritos2020 | Pituitary, Vol. 23, No. 3MRI radiomics for the prediction of recurrence in patients with clinically non-functioning pituitary macroadenomasLeonardo F.Machado, Paula C.L.Elias, Ayrton C.Moreira, Antônio C.dos Santos, Luiz O.Murta Junior2020 | Computers in Biology and Medicine, Vol. 124Radiomics and Artificial Intelligence for Renal Mass CharacterizationMeghan G.Lubner2020 | Radiologic Clinics of North America, Vol. 58, No. 5The potential of machine learning to predict postoperative pancreatic fistula based on preoperative, non-contrast-enhanced CT: A proof-of-principle studyPatrykKambakamba, ManojMannil, Paola E.Herrera, Philip C.Müller, ChristophKuemmerli, MichaelLinecker, Jochenvon Spiczak, Martin W.Hüllner, Dimitri A.Raptis, HenrikPetrowsky, Pierre-AlainClavien, HatemAlkadhi2020 | Surgery, Vol. 167, No. 2Discriminating pseudoprogression and true progression in diffuse infiltrating glioma using multi-parametric MRI data through deep learningJoonsangLee, NicholasWang, SevcanTurk, ShariqMohammed, RemyLobo, JohnKim, EricLiao, SandraCamelo-Piragua, MichelleKim, LarryJunck, JayapalliBapuraj, AshokSrinivasan, ArvindRao2020 | Scientific Reports, Vol. 10, No. 1Radiomics in medical imaging—"how-to" guide and critical reflectionJanita E.van Timmeren, DavideCester, StephanieTanadini-Lang, HatemAlkadhi, BettinaBaessler2020 | Insights into Imaging, Vol. 11, No. 1Differentiating High-Grade Gliomas from Brain Metastases at Magnetic Resonance: The Role of Texture Analysis of the Peritumoral ZoneCsabaCsutak, Paul-AndreiȘtefan, Lavinia ManuelaLenghel, Cezar OctavianMoroșanu, Roxana-AdelinaLupean, LarisaȘimonca, Carmen MihaelaMihu, AndreiLebovici2020 | Brain Sciences, Vol. 10, No. 9Computed tomography texture features can discriminate benign from malignant lymphadenopathy in pediatric patients: a preliminary studyAlexis M.Cahalane, AoifeKilcoyne, AzadehTabari, ShaunaghMcDermott, Michael S.Gee2019 | Pediatric Radiology, Vol. 49, No. 6Prediction of liver remnant regeneration after living donor liver transplantation using preoperative CT texture analysisJi-EunKim, Jung HoonKim, Sang JoonPark, Seo-YounChoi, Nam-JoonYi, Joon KooHan2019 | Abdominal Radiology, Vol. 44, No. 5Correlation of texture analysis of paraspinal musculature on MRI with different clinical endpoints: Lumbar Stenosis Outcome Study (LSOS)ManojMannil, Jakob M.Burgstaller, UlrikeHeld, MazdaFarshad, RomanGuggenberger2019 | European Radiology, Vol. 29, No. 1Classification Techniques for Medical Image Analysis and Computer Aided DiagnosisIndrajeetKumar, JitendraVirmani, H.S.Bhadauria, ShrutiThakur2019Radiomics and Artificial Intelligence for Biomarker and Prediction Model Development in OncologyRezaForghani, PeterSavadjiev, AvishekChatterjee, NikeshMuthukrishnan, CarolineReinhold, BehzadForghani2019 | Computational and Structural Biotechnology Journal, Vol. 17Automated brain tumor segmentation from multimodal MRI data based on Tamura texture feature and an ensemble SVM classifierLiNa, XiongZhiyong, DengTianqi, RenKai2019 | International Journal of Intelligent Computing and Cybernetics, Vol. 12, No. 4Diagnostic Value of Machine Learning-Based Quantitative Texture Analysis in Differentiating Benign and Malignant Thyroid NodulesBulentColakoglu, DenizAlis, MertYergin2019 | Journal of Oncology, Vol. 2019Machine learning in cardiovascular magnetic resonance: basic concepts and applicationsTimLeiner, DanielRueckert, AvanSuinesiaputra, BettinaBaeßler, RezaNezafat, IvanaIšgum, Alistair A.Young2019 | Journal of Cardiovascular Magnetic Resonance, Vol. 21, No. 1A whole slide image-based machine learning approach to predict ductal carcinoma in situ (DCIS) recurrence riskSergeyKlimov, Islam M.Miligy, ArkadiuszGertych, YiJiang, Michael S.Toss, PadmashreeRida, Ian O.Ellis, AndrewGreen, UmaKrishnamurti, Emad A.Rakha, RituAneja2019 | Breast Cancer Research, Vol. 21, No. 1A Novel Run-length based wavelet features for Screening Thyroid Nodule MalignancySalih OmerHaji, Raghad ZuhairYousif2019 | Brazilian Archives of Biology and Technology, Vol. 62Subacute and Chronic Left Ventricular Myocardial Scar: Accuracy of Texture Analysis on Nonenhanced Cine MR ImagesBettina Baessler, Manoj Mannil, Sabrina Oebel, David Maintz, Hatem Alkadhi, Robert Manka, 23 August 2017 | Radiology, Vol. 286, No. 1Communications in Computer and Information ScienceAbdullahAlfahaid, TimMorris2018 | , Vol. 894Soft Computing Based Medical Image AnalysisIndrajeetKumar, JitendraVirmani, Harvendra S.Bhadauria, Manoj K.Panda, Kriti2018Texture analysis and machine learning of non-contrast T1-weighted MR images in patients with hypertrophic cardiomyopathy—Preliminary resultsBettinaBaeßler, ManojMannil, DavidMaintz, HatemAlkadhi, RobertManka2018 | European Journal of Radiology, Vol. 102MRI texture analysis as a predictor of tumor recurrence or progression in patients with clinically non-functioning pituitary adenomasBrandon PGalm, E LeonardoMartinez-Salazar, BrookeSwearingen, MartinTorriani, AnneKlibanski, Miriam ABredella, Nicholas ATritos2018 | European Journal of Endocrinology, Vol. 179, No. 3Imaging Genetic Heterogeneity in Glioblastoma and Other Glial Tumors: Review of Current Methods and Future DirectionsDanielChow, PeterChang, Brent D.Weinberg, Daniela A.Bota, JackGrinband, Christopher G.Filippi2018 | American Journal of Roentgenology, Vol. 210, No. 1Automated and effective content-based image retrieval for digital mammographyVibhav PrakashSingh, SubodhSrivastava, RajeevSrivastava2018 | Journal of X-Ray Science and Technology, Vol. 26, No. 1Investigation of the radiotherapy-related changes in the eye lens using computed tomography entropy analysisNeslihanKurtul, NurselYurttutan, MuratBaykara2018 | Journal of X-Ray Science and Technology, Vol. 26, No. 5Anorexia Nervosa: Analysis of Trabecular Texture with CTAzadeh Tabari, Martin Torriani, Karen K. Miller, Anne Klibanski, Mannudeep K. Kalra, Miriam A. Bredella, 31 October 2016 | Radiology, Vol. 283, No. 1Normative values for CT-based texture analysis of vertebral bodies in dual X-ray absorptiometry-confirmed, normally mineralized subjectsManojMannil, MatthiasEberhard, Anton S.Becker, DeniseSchönenberg, GeorgOsterhoff, Diana P.Frey, EnderKonukoglu, HatemAlkadhi, RomanGuggenberger2017 | Skeletal Radiology, Vol. 46, No. 11Texture analysis in radiology: Does the emperor have no clothes?Ronald M.Summers2017 | Abdominal Radiology, Vol. 42, No. 2A hybrid hierarchical framework for classification of breast density using digitized film screen mammogramsIndrajeetKumar, H. S.Bhadauria, JitendraVirmani, ShrutiThakur2017 | Multimedia Tools and Applications, Vol. 76, No. 18Biomedical Texture AnalysisAdrienDepeursinge, JulienFageot, Omar S.Al-Kadi2017Biomedical Texture AnalysisJie-ZhiCheng, Chung-MingChen, DinggangShen2017Evaluation of Texture Analysis Parameter for Response Prediction in Patients with Hepatocellular Carcinoma Undergoing Drug-eluting Bead Transarterial Chemoembolization (DEB-TACE) Using Biphasic Contrast-enhanced CT Image DataChristopherKloth, Wolfgang M.Thaiss, RainerKärgel, RainerGrimmer, JanFritz, Sorin DumitruIoanoviciu, DominikKetelsen, KonstantinNikolaou, MariusHorger2017 | Academic Radiology, Vol. 24, No. 11Differences in Texture Analysis Parameters Between Active Alveolitis and Lung Fibrosis in Chest CT of Patients with Systemic SclerosisChristopherKloth, Anya C.Blum, Wolfgang M.Thaiss, HeikePreibsch, HendrikDitt, RainerGrimmer, JanFritz, KonstantinNikolaou, HansBösmüller, MariusHorger2017 | Academic Radiology, Vol. 24, No. 12A classification framework for prediction of breast density using an ensemble of neural network classifiersIndrajeetKumar, BhadauriaH.S., JitendraVirmani, ShrutiThakur2017 | Biocybernetics and Biomedical Engineering, Vol. 37, No. 1A deep learning framework for supporting the classification of breast lesions in ultrasound imagesSeokminHan, Ho-KyungKang, Ja-YeonJeong, Moon-HoPark, WonsikKim, Won-ChulBang, Yeong-KyeongSeong2017 | Physics in Medicine & Biology, Vol. 62, No. 19Tumor spatial heterogeneity in myxoid-containing soft tissue using texture analysis of diffusion-weighted MRIHyun SuKim, Jae-HunKim, Young CheolYoon, Bong KeunChoe, CongCao2017 | PLOS ONE, Vol. 12, No. 7Medical ImagingJane DominiqueMoon, Mary P.Galea2017Hybrid Intelligence for Image Analysis and UnderstandingKriti, HarleenKaur, JitendraVirmani2017Malignancy characterization of hepatocellular carcinomas based on texture analysis of contrast‐enhanced MR imagesWuZhou, LijuanZhang, KaixinWang, ShutingChen, GuangyiWang, ZaiyiLiu, ChanghongLiang2017 | Journal of Magnetic Resonance Imaging, Vol. 45, No. 5Studies in Computational IntelligenceKriti, JitendraVirmani, ShrutiThakur2016 | , Vol. 630Studies in Computational IntelligenceKriti, JitendraVirmani2016 | , Vol. 651Studies in Computational IntelligenceAhmed M.Anter, Aboul EllaHassenian2016 | , Vol. 651Magnetic resonance imaging texture analysis classification of primary breast cancerS. A.Waugh, C. A.Purdie, L. B.Jordan, S.Vinnicombe, R. A.Lerski, P.Martin, A. M.Thompson2016 | European Radiology, Vol. 26, No. 2Advances in Healthcare Information Systems and AdministrationJane DominiqueMoon, Mary P.Galea2016Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT ScansJie-ZhiCheng, DongNi, Yi-HongChou, JingQin, Chui-MeiTiu, Yeun-ChungChang, Chiun-ShengHuang, DinggangShen, Chung-MingChen2016 | Scientific Reports, Vol. 6, No. 1Intelligent Systems Reference LibraryKriti, JitendraVirmani, NilanjanDey, VinodKumar2016 | , Vol. 96Can Quantitative CT Texture Analysis be Used to Differentiate Fat-poor Renal Angiomyolipoma from Renal Cell Carcinoma on Unenhanced CT Images?Taryn Hodgdon, Matthew D. F. McInnes, Nicola Schieda, Trevor A. Flood, Leslie Lamb, Rebecca E. Thornhill, 23 April 2015 | Radiology, Vol. 276, No. 3Use of TrueBeam developer mode for imaging QAGilmerValdes, OlivierMorin, YanisleyValenciaga, NielKirby, JeanPouliot, CynthiaChuang8 July 2015 | Journal of Applied Clinical Medical Physics, Vol. 16, No. 4Quantitative CT texture and shape analysis: Can it differentiate benign and malignant mediastinal lymph nodes in patients with primary lung cancer?HamidBayanati, RebeccaE. Thornhill, Carolina A.Souza, VineetaSethi-Virmani, AshishGupta, DonnaMaziak, KayvanAmjadi, CaroleDennie2015 | European Radiology, Vol. 25, No. 2BIPCO: ultrasound feature points based on phase congruency detector and binary pattern descriptorDiegoDall'Alba, PaoloFiorini2015 | International Journal of Computer Assisted Radiology and Surgery, Vol. 10, No. 6Differentiation of true-progression from pseudoprogression in glioblastoma treated with radiation therapy and concomitant temozolomide by GLCM texture analysis of conventional MRIXinChen, XinhuaWei, ZhongpingZhang, RuimengYang, YanjieZhu, XinqingJiang2015 | Clinical Imaging, Vol. 39, No. 5Locality-constrained Subcluster Representation Ensemble for lung image classificationYangSong, WeidongCai, HengHuang, YunZhou, YueWang, David DaganFeng2015 | Medical Image Analysis, Vol. 22, No. 12015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)AhmadChaddad, Pascal O.Zinn, Rivka R.Colen2015Medical Imaging 2015: Computer-Aided DiagnosisLubomir M.Hadjiiski, Georgia D.Tourassi, S.Li, A.Lin, K.Tay, W.Romano, SaidOsman2015 | , Vol. 9414Telemedicine and Electronic MedicineMohitKumar, NorbertStoll, KerstinThurow, ReginaStoll2015Diagnosis of Sarcomatoid Renal Cell Carcinoma With CT: Evaluation by Qualitative Imaging Features and Texture AnalysisNicolaSchieda, Rebecca E.Thornhill, MaaliA

Referência(s)
Altmetric
PlumX