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Items: 4

1.

A Deep Convolutional Neural Network for Annotation of Magnetic Resonance Imaging Sequence Type.

Ranjbar S, Singleton KW, Jackson PR, Rickertsen CR, Whitmire SA, Clark-Swanson KR, Mitchell JR, Swanson KR, Hu LS.

J Digit Imaging. 2019 Oct 25. doi: 10.1007/s10278-019-00282-4. [Epub ahead of print]

PMID:
31654174
2.

Multiparameter MRI Predictors of Long-Term Survival in Glioblastoma Multiforme.

Stringfield O, Arrington JA, Johnston SK, Rognin NG, Peeri NC, Balagurunathan Y, Jackson PR, Clark-Swanson KR, Swanson KR, Egan KM, Gatenby RA, Raghunand N.

Tomography. 2019 Mar;5(1):135-144. doi: 10.18383/j.tom.2018.00052.

3.

Distinct Phenotypic Clusters of Glioblastoma Growth and Response Kinetics Predict Survival.

Rayfield CA, Grady F, De Leon G, Rockne R, Carrasco E, Jackson P, Vora M, Johnston SK, Hawkins-Daarud A, Clark-Swanson KR, Whitmire S, Gamez ME, Porter A, Hu L, Gonzalez-Cuyar L, Bendok B, Vora S, Swanson KR.

JCO Clin Cancer Inform. 2018 Dec;2:1-14. doi: 10.1200/CCI.17.00080.

4.

Patient-specific metrics of invasiveness reveal significant prognostic benefit of resection in a predictable subset of gliomas.

Baldock AL, Ahn S, Rockne R, Johnston S, Neal M, Corwin D, Clark-Swanson K, Sterin G, Trister AD, Malone H, Ebiana V, Sonabend AM, Mrugala M, Rockhill JK, Silbergeld DL, Lai A, Cloughesy T, McKhann GM 2nd, Bruce JN, Rostomily RC, Canoll P, Swanson KR.

PLoS One. 2014 Oct 28;9(10):e99057. doi: 10.1371/journal.pone.0099057. eCollection 2014.

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