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Items: 1 to 50 of 198

1.

Risk factors and epidemiologic predictors of blood stream infections with New Delhi Metallo-b-lactamase (NDM-1) producing Enterobacteriaceae.

Snyder BM, Montague BT, Anandan S, Madabhushi AG, Pragasam AK, Verghese VP, Balaji V, Simões EAF.

Epidemiol Infect. 2019 Jan;147:e137. doi: 10.1017/S0950268819000256.

PMID:
30869056
2.

Correlation between MRI phenotypes and a genomic classifier of prostate cancer: preliminary findings.

Purysko AS, Magi-Galluzzi C, Mian OY, Sittenfeld S, Davicioni E, du Plessis M, Buerki C, Bullen J, Li L, Madabhushi A, Stephenson A, Klein EA.

Eur Radiol. 2019 Mar 7. doi: 10.1007/s00330-019-06114-x. [Epub ahead of print]

PMID:
30847589
3.

Convolutional neural network initialized active contour model with adaptive ellipse fitting for nuclear segmentation on breast histopathological images.

Xu J, Gong L, Wang G, Lu C, Gilmore H, Zhang S, Madabhushi A.

J Med Imaging (Bellingham). 2019 Jan;6(1):017501. doi: 10.1117/1.JMI.6.1.017501. Epub 2019 Feb 8.

PMID:
30840729
4.

Comparing radiomic classifiers and classifier ensembles for detection of peripheral zone prostate tumors on T2-weighted MRI: a multi-site study.

Viswanath SE, Chirra PV, Yim MC, Rofsky NM, Purysko AS, Rosen MA, Bloch BN, Madabhushi A.

BMC Med Imaging. 2019 Feb 28;19(1):22. doi: 10.1186/s12880-019-0308-6.

5.

Disorder in Pixel-Level Edge Directions on T1WI Is Associated with the Degree of Radiation Necrosis in Primary and Metastatic Brain Tumors: Preliminary Findings.

Prasanna P, Rogers L, Lam TC, Cohen M, Siddalingappa A, Wolansky L, Pinho M, Gupta A, Hatanpaa KJ, Madabhushi A, Tiwari P.

AJNR Am J Neuroradiol. 2019 Mar;40(3):412-417. doi: 10.3174/ajnr.A5958. Epub 2019 Feb 7.

PMID:
30733252
6.

Mass Effect Deformation Heterogeneity (MEDH) on Gadolinium-contrast T1-weighted MRI is associated with decreased survival in patients with right cerebral hemisphere Glioblastoma: A feasibility study.

Prasanna P, Mitra J, Beig N, Nayate A, Patel J, Ghose S, Thawani R, Partovi S, Madabhushi A, Tiwari P.

Sci Rep. 2019 Feb 4;9(1):1145. doi: 10.1038/s41598-018-37615-2.

7.

Quantitative Image Analysis of Human Epidermal Growth Factor Receptor 2 Immunohistochemistry for Breast Cancer: Guideline From the College of American Pathologists.

Bui MM, Riben MW, Allison KH, Chlipala E, Colasacco C, Kahn AG, Lacchetti C, Madabhushi A, Pantanowitz L, Salama ME, Stewart RL, Thomas NE, Tomaszewski JE, Hammond ME.

Arch Pathol Lab Med. 2019 Jan 15. doi: 10.5858/arpa.2018-0378-CP. [Epub ahead of print]

PMID:
30645156
8.

Computer-Aided Laser Dissection: A Microdissection Workflow Leveraging Image Analysis Tools.

Hipp JD, Johann DJ, Chen Y, Madabhushi A, Monaco J, Cheng J, Rodriguez-Canales J, Stumpe MC, Riedlinger G, Rosenberg AZ, Hanson JC, Kunju LP, Emmert-Buck MR, Balis UJ, Tangrea MA.

J Pathol Inform. 2018 Dec 11;9:45. doi: 10.4103/jpi.jpi_60_18. eCollection 2018.

9.

Perinodular and Intranodular Radiomic Features on Lung CT Images Distinguish Adenocarcinomas from Granulomas.

Beig N, Khorrami M, Alilou M, Prasanna P, Braman N, Orooji M, Rakshit S, Bera K, Rajiah P, Ginsberg J, Donatelli C, Thawani R, Yang M, Jacono F, Tiwari P, Velcheti V, Gilkeson R, Linden P, Madabhushi A.

Radiology. 2019 Mar;290(3):783-792. doi: 10.1148/radiol.2018180910. Epub 2018 Dec 18.

10.

Shape Features of the Lesion Habitat to Differentiate Brain Tumor Progression from Pseudoprogression on Routine Multiparametric MRI: A Multisite Study.

Ismail M, Hill V, Statsevych V, Huang R, Prasanna P, Correa R, Singh G, Bera K, Beig N, Thawani R, Madabhushi A, Aahluwalia M, Tiwari P.

AJNR Am J Neuroradiol. 2018 Dec;39(12):2187-2193. doi: 10.3174/ajnr.A5858. Epub 2018 Nov 1.

PMID:
30385468
11.

Quantitative vessel tortuosity: A potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomas.

Alilou M, Orooji M, Beig N, Prasanna P, Rajiah P, Donatelli C, Velcheti V, Rakshit S, Yang M, Jacono F, Gilkeson R, Linden P, Madabhushi A.

Sci Rep. 2018 Oct 16;8(1):15290. doi: 10.1038/s41598-018-33473-0.

12.

Stable and discriminating features are predictive of cancer presence and Gleason grade in radical prostatectomy specimens: a multi-site study.

Leo P, Elliott R, Shih NNC, Gupta S, Feldman M, Madabhushi A.

Sci Rep. 2018 Oct 8;8(1):14918. doi: 10.1038/s41598-018-33026-5.

13.

Novel Quantitative Imaging for Predicting Response to Therapy: Techniques and Clinical Applications.

Bera K, Velcheti V, Madabhushi A.

Am Soc Clin Oncol Educ Book. 2018 May 23;(38):1008-1018. doi: 10.1200/EDBK_199747. Review.

14.

Spatial Architecture and Arrangement of Tumor-Infiltrating Lymphocytes for Predicting Likelihood of Recurrence in Early-Stage Non-Small Cell Lung Cancer.

Corredor G, Wang X, Zhou Y, Lu C, Fu P, Syrigos K, Rimm DL, Yang M, Romero E, Schalper KA, Velcheti V, Madabhushi A.

Clin Cancer Res. 2019 Mar 1;25(5):1526-1534. doi: 10.1158/1078-0432.CCR-18-2013. Epub 2018 Sep 10.

PMID:
30201760
15.

Identifying the morphologic basis for radiomic features in distinguishing different Gleason grades of prostate cancer on MRI: Preliminary findings.

Penzias G, Singanamalli A, Elliott R, Gollamudi J, Shih N, Feldman M, Stricker PD, Delprado W, Tiwari S, Böhm M, Haynes AM, Ponsky L, Fu P, Tiwari P, Viswanath S, Madabhushi A.

PLoS One. 2018 Aug 31;13(8):e0200730. doi: 10.1371/journal.pone.0200730. eCollection 2018.

16.

Nuclear shape and orientation features from H&E images predict survival in early-stage estrogen receptor-positive breast cancers.

Lu C, Romo-Bucheli D, Wang X, Janowczyk A, Ganesan S, Gilmore H, Rimm D, Madabhushi A.

Lab Invest. 2018 Nov;98(11):1438-1448. doi: 10.1038/s41374-018-0095-7. Epub 2018 Jun 29.

17.

Advances in the computational and molecular understanding of the prostate cancer cell nucleus.

Carleton NM, Lee G, Madabhushi A, Veltri RW.

J Cell Biochem. 2018 Sep;119(9):7127-7142. doi: 10.1002/jcb.27156. Epub 2018 Jun 20.

PMID:
29923622
18.

Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer.

Whitney J, Corredor G, Janowczyk A, Ganesan S, Doyle S, Tomaszewski J, Feldman M, Gilmore H, Madabhushi A.

BMC Cancer. 2018 May 30;18(1):610. doi: 10.1186/s12885-018-4448-9.

19.

High-throughput adaptive sampling for whole-slide histopathology image analysis (HASHI) via convolutional neural networks: Application to invasive breast cancer detection.

Cruz-Roa A, Gilmore H, Basavanhally A, Feldman M, Ganesan S, Shih N, Tomaszewski J, Madabhushi A, González F.

PLoS One. 2018 May 24;13(5):e0196828. doi: 10.1371/journal.pone.0196828. eCollection 2018.

20.

Radiomic features from pretreatment biparametric MRI predict prostate cancer biochemical recurrence: Preliminary findings.

Shiradkar R, Ghose S, Jambor I, Taimen P, Ettala O, Purysko AS, Madabhushi A.

J Magn Reson Imaging. 2018 Dec;48(6):1626-1636. doi: 10.1002/jmri.26178. Epub 2018 May 7.

PMID:
29734484
21.

A resolution adaptive deep hierarchical (RADHicaL) learning scheme applied to nuclear segmentation of digital pathology images.

Janowczyk A, Doyle S, Gilmore H, Madabhushi A.

Comput Methods Biomech Biomed Eng Imaging Vis. 2018;6(3):270-276. doi: 10.1080/21681163.2016.1141063. Epub 2016 Apr 28.

22.

Combination of computer extracted shape and texture features enables discrimination of granulomas from adenocarcinoma on chest computed tomography.

Orooji M, Alilou M, Rakshit S, Beig N, Khorrami MH, Rajiah P, Thawani R, Ginsberg J, Donatelli C, Yang M, Jacono F, Gilkeson R, Velcheti V, Linden P, Madabhushi A.

J Med Imaging (Bellingham). 2018 Apr;5(2):024501. doi: 10.1117/1.JMI.5.2.024501. Epub 2018 Apr 18.

PMID:
29721515
23.

A deep-learning classifier identifies patients with clinical heart failure using whole-slide images of H&E tissue.

Nirschl JJ, Janowczyk A, Peyster EG, Frank R, Margulies KB, Feldman MD, Madabhushi A.

PLoS One. 2018 Apr 3;13(4):e0192726. doi: 10.1371/journal.pone.0192726. eCollection 2018.

24.

Advanced Morphologic Analysis for Diagnosing Allograft Rejection: The Case of Cardiac Transplant Rejection.

Peyster EG, Madabhushi A, Margulies KB.

Transplantation. 2018 Aug;102(8):1230-1239. doi: 10.1097/TP.0000000000002189.

25.

Radiomic features on MRI enable risk categorization of prostate cancer patients on active surveillance: Preliminary findings.

Algohary A, Viswanath S, Shiradkar R, Ghose S, Pahwa S, Moses D, Jambor I, Shnier R, Böhm M, Haynes AM, Brenner P, Delprado W, Thompson J, Pulbrock M, Purysko AS, Verma S, Ponsky L, Stricker P, Madabhushi A.

J Magn Reson Imaging. 2018 Feb 22. doi: 10.1002/jmri.25983. [Epub ahead of print]

PMID:
29469937
26.

Coregistration of Preoperative MRI with Ex Vivo Mesorectal Pathology Specimens to Spatially Map Post-treatment Changes in Rectal Cancer Onto In Vivo Imaging: Preliminary Findings.

Antunes J, Viswanath S, Brady JT, Crawshaw B, Ros P, Steele S, Delaney CP, Paspulati R, Willis J, Madabhushi A.

Acad Radiol. 2018 Jul;25(7):833-841. doi: 10.1016/j.acra.2017.12.006. Epub 2018 Jan 19.

27.

Radiogenomic analysis of hypoxia pathway is predictive of overall survival in Glioblastoma.

Beig N, Patel J, Prasanna P, Hill V, Gupta A, Correa R, Bera K, Singh S, Partovi S, Varadan V, Ahluwalia M, Madabhushi A, Tiwari P.

Sci Rep. 2018 Jan 8;8(1):7. doi: 10.1038/s41598-017-18310-0.

28.

Radiomics and radiogenomics in lung cancer: A review for the clinician.

Thawani R, McLane M, Beig N, Ghose S, Prasanna P, Velcheti V, Madabhushi A.

Lung Cancer. 2018 Jan;115:34-41. doi: 10.1016/j.lungcan.2017.10.015. Epub 2017 Nov 8. Review.

PMID:
29290259
29.

Prostate shapes on pre-treatment MRI between prostate cancer patients who do and do not undergo biochemical recurrence are different: Preliminary Findings.

Ghose S, Shiradkar R, Rusu M, Mitra J, Thawani R, Feldman M, Gupta AC, Purysko AS, Ponsky L, Madabhushi A.

Sci Rep. 2017 Nov 20;7(1):15829. doi: 10.1038/s41598-017-13443-8.

30.

An Image Analysis Resource for Cancer Research: PIIP-Pathology Image Informatics Platform for Visualization, Analysis, and Management.

Martel AL, Hosseinzadeh D, Senaras C, Zhou Y, Yazdanpanah A, Shojaii R, Patterson ES, Madabhushi A, Gurcan MN.

Cancer Res. 2017 Nov 1;77(21):e83-e86. doi: 10.1158/0008-5472.CAN-17-0323.

31.

Prediction of recurrence in early stage non-small cell lung cancer using computer extracted nuclear features from digital H&E images.

Wang X, Janowczyk A, Zhou Y, Thawani R, Fu P, Schalper K, Velcheti V, Madabhushi A.

Sci Rep. 2017 Oct 19;7(1):13543. doi: 10.1038/s41598-017-13773-7.

32.

Discriminative Scale Learning (DiScrn): Applications to Prostate Cancer Detection from MRI and Needle Biopsies.

Wang H, Viswanath S, Madabhushi A.

Sci Rep. 2017 Sep 28;7(1):12375. doi: 10.1038/s41598-017-12569-z.

33.

Reply.

Tiwari P, Madabhushi A.

AJNR Am J Neuroradiol. 2017 Nov;38(11):E94. doi: 10.3174/ajnr.A5366. Epub 2017 Aug 31. No abstract available.

34.

Co-Registration of ex vivo Surgical Histopathology and in vivo T2 weighted MRI of the Prostate via multi-scale spectral embedding representation.

Li L, Pahwa S, Penzias G, Rusu M, Gollamudi J, Viswanath S, Madabhushi A.

Sci Rep. 2017 Aug 18;7(1):8717. doi: 10.1038/s41598-017-08969-w.

35.

Cascaded Multi-view Canonical Correlation (CaMCCo) for Early Diagnosis of Alzheimer's Disease via Fusion of Clinical, Imaging and Omic Features.

Singanamalli A, Wang H, Madabhushi A; Alzheimer’s Disease Neuroimaging Initiative.

Sci Rep. 2017 Aug 15;7(1):8137. doi: 10.1038/s41598-017-03925-0.

36.

Single cell qPCR reveals that additional HAND2 and microRNA-1 facilitate the early reprogramming progress of seven-factor-induced human myocytes.

Bektik E, Dennis A, Prasanna P, Madabhushi A, Fu JD.

PLoS One. 2017 Aug 10;12(8):e0183000. doi: 10.1371/journal.pone.0183000. eCollection 2017.

37.

An oral cavity squamous cell carcinoma quantitative histomorphometric-based image classifier of nuclear morphology can risk stratify patients for disease-specific survival.

Lu C, Lewis JS Jr, Dupont WD, Plummer WD Jr, Janowczyk A, Madabhushi A.

Mod Pathol. 2017 Dec;30(12):1655-1665. doi: 10.1038/modpathol.2017.98. Epub 2017 Aug 4.

38.

Nuclear Shape and Architecture in Benign Fields Predict Biochemical Recurrence in Prostate Cancer Patients Following Radical Prostatectomy: Preliminary Findings.

Lee G, Veltri RW, Zhu G, Ali S, Epstein JI, Madabhushi A.

Eur Urol Focus. 2017 Oct;3(4-5):457-466. doi: 10.1016/j.euf.2016.05.009. Epub 2016 Jun 16.

39.

Erratum to: Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI.

Braman NM, Etesami M, Prasanna P, Dubchuk C, Gilmore H, Tiwari P, Plecha D, Madabhushi A.

Breast Cancer Res. 2017 Jul 10;19(1):80. doi: 10.1186/s13058-017-0862-1. No abstract available.

40.

Special Section Guest Editorial: Digital Pathology.

Gurcan MN, Tomaszewski JE, Madabhushi A.

J Med Imaging (Bellingham). 2017 Apr;4(2):021101. doi: 10.1117/1.JMI.4.2.021101. Epub 2017 Jun 28. No abstract available.

41.

Erratum to: Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings.

Prasanna P, Patel J, Partovi S, Madabhushi A, Tiwari P.

Eur Radiol. 2017 Oct;27(10):4198-4199. doi: 10.1007/s00330-017-4815-y. Epub 2017 Jun 12. No abstract available.

PMID:
28608160
42.

Intratumoral and peritumoral radiomics for the pretreatment prediction of pathological complete response to neoadjuvant chemotherapy based on breast DCE-MRI.

Braman NM, Etesami M, Prasanna P, Dubchuk C, Gilmore H, Tiwari P, Plecha D, Madabhushi A.

Breast Cancer Res. 2017 May 18;19(1):57. doi: 10.1186/s13058-017-0846-1. Erratum in: Breast Cancer Res. 2017 Jul 10;19(1):80.

43.

Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent.

Cruz-Roa A, Gilmore H, Basavanhally A, Feldman M, Ganesan S, Shih NNC, Tomaszewski J, González FA, Madabhushi A.

Sci Rep. 2017 Apr 18;7:46450. doi: 10.1038/srep46450.

44.

Co-registration of pre-operative CT with ex vivo surgically excised ground glass nodules to define spatial extent of invasive adenocarcinoma on in vivo imaging: a proof-of-concept study.

Rusu M, Rajiah P, Gilkeson R, Yang M, Donatelli C, Thawani R, Jacono FJ, Linden P, Madabhushi A.

Eur Radiol. 2017 Oct;27(10):4209-4217. doi: 10.1007/s00330-017-4813-0. Epub 2017 Apr 6.

45.

Connecting Markov random fields and active contour models: application to gland segmentation and classification.

Xu J, Monaco JP, Sparks R, Madabhushi A.

J Med Imaging (Bellingham). 2017 Apr;4(2):021107. doi: 10.1117/1.JMI.4.2.021107. Epub 2017 Mar 28.

46.

Training a cell-level classifier for detecting basal-cell carcinoma by combining human visual attention maps with low-level handcrafted features.

Corredor G, Whitney J, Arias V, Madabhushi A, Romero E.

J Med Imaging (Bellingham). 2017 Apr;4(2):021105. doi: 10.1117/1.JMI.4.2.021105. Epub 2017 Mar 11.

47.

An integrated segmentation and shape-based classification scheme for distinguishing adenocarcinomas from granulomas on lung CT.

Alilou M, Beig N, Orooji M, Rajiah P, Velcheti V, Rakshit S, Reddy N, Yang M, Jacono F, Gilkeson RC, Linden P, Madabhushi A.

Med Phys. 2017 Jul;44(7):3556-3569. doi: 10.1002/mp.12208. Epub 2017 May 23.

48.

A deep learning based strategy for identifying and associating mitotic activity with gene expression derived risk categories in estrogen receptor positive breast cancers.

Romo-Bucheli D, Janowczyk A, Gilmore H, Romero E, Madabhushi A.

Cytometry A. 2017 Jun;91(6):566-573. doi: 10.1002/cyto.a.23065. Epub 2017 Feb 13.

49.

A Deep Convolutional Neural Network for segmenting and classifying epithelial and stromal regions in histopathological images.

Xu J, Luo X, Wang G, Gilmore H, Madabhushi A.

Neurocomputing. 2016 May 26;191:214-223. doi: 10.1016/j.neucom.2016.01.034. Epub 2016 Feb 17.

50.

Computational imaging reveals shape differences between normal and malignant prostates on MRI.

Rusu M, Purysko AS, Verma S, Kiechle J, Gollamudi J, Ghose S, Herrmann K, Gulani V, Paspulati R, Ponsky L, Böhm M, Haynes AM, Moses D, Shnier R, Delprado W, Thompson J, Stricker P, Madabhushi A.

Sci Rep. 2017 Feb 1;7:41261. doi: 10.1038/srep41261.

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