Haas M - Search Results

1

Interactive Explainable Deep Learning Model Informs Prostate Cancer Diagnosis at MRI.

Hamm CA, Baumgärtner GL, Biessmann F, Beetz NL, Hartenstein A, Savic LJ, Froböse K, Dräger F, Schallenberg S, Rudolph M, Baur ADJ, Hamm B, Haas M, Hofbauer S, Cash H, Penzkofer T. Hamm CA, et al. Among authors: haas m. Radiology. 2023 May;307(4):e222276. doi: 10.1148/radiol.222276. Epub 2023 Apr 11. Radiology. 2023. PMID: 37039688

2

Validation of the PI-RADS language: predictive values of PI-RADS lexicon descriptors for detection of prostate cancer.

Rudolph MM, Baur ADJ, Haas M, Cash H, Miller K, Mahjoub S, Hartenstein A, Kaufmann D, Rotzinger R, Lee CH, Asbach P, Hamm B, Penzkofer T. Rudolph MM, et al. Among authors: haas m. Eur Radiol. 2020 Aug;30(8):4262-4271. doi: 10.1007/s00330-020-06773-1. Epub 2020 Mar 26. Eur Radiol. 2020. PMID: 32219507 Free PMC article.

3

Optimizing size thresholds for detection of clinically significant prostate cancer on MRI: Peripheral zone cancers are smaller and more predictable than transition zone tumors.

Mahjoub S, Baur ADJ, Lenk J, Lee CH, Hartenstein A, Rudolph MM, Cash H, Hamm B, Asbach P, Haas M, Penzkofer T. Mahjoub S, et al. Among authors: haas m. Eur J Radiol. 2020 Aug;129:109071. doi: 10.1016/j.ejrad.2020.109071. Epub 2020 May 17. Eur J Radiol. 2020. PMID: 32531720

4

Automated lung volumetry from routine thoracic CT scans: how reliable is the result?

Haas M, Hamm B, Niehues SM. Haas M, et al. Acad Radiol. 2014 May;21(5):633-8. doi: 10.1016/j.acra.2014.01.002. Acad Radiol. 2014. PMID: 24703476

5

Diagnostic performance of PI-RADS version 2.1 compared to version 2.0 for detection of peripheral and transition zone prostate cancer.

Rudolph MM, Baur ADJ, Cash H, Haas M, Mahjoub S, Hartenstein A, Hamm CA, Beetz NL, Konietschke F, Hamm B, Asbach P, Penzkofer T. Rudolph MM, et al. Among authors: haas m. Sci Rep. 2020 Sep 29;10(1):15982. doi: 10.1038/s41598-020-72544-z. Sci Rep. 2020. PMID: 32994502 Free PMC article.

6

MRI-targeted biopsy cores from prostate index lesions: assessment and prediction of the number needed.

Beetz NL, Dräger F, Hamm CA, Shnayien S, Rudolph MM, Froböse K, Elezkurtaj S, Haas M, Asbach P, Hamm B, Mahjoub S, Konietschke F, Wechsung M, Balzer F, Cash H, Hofbauer S, Penzkofer T. Beetz NL, et al. Among authors: haas m. Prostate Cancer Prostatic Dis. 2023 Sep;26(3):543-551. doi: 10.1038/s41391-022-00599-2. Epub 2022 Oct 8. Prostate Cancer Prostatic Dis. 2023. PMID: 36209237 Free PMC article.

7

[MR imaging of the prostate].

Asbach P, Haas M, Hamm B. Asbach P, et al. Among authors: haas m. Radiologe. 2015 Dec;55(12):1088-96. doi: 10.1007/s00117-015-0035-0. Radiologe. 2015. PMID: 26515285 Review. German.

8

Is the Ellipsoid Formula the New Standard for 3-Tesla MRI Prostate Volume Calculation without Endorectal Coil?

Haas M, Günzel K, Miller K, Hamm B, Cash H, Asbach P. Haas M, et al. Urol Int. 2017;98(1):49-53. doi: 10.1159/000448593. Epub 2016 Sep 15. Urol Int. 2017. PMID: 27627060

9

[Implications of PI-RADS Version 1 and Updated Version 2 on the Scoring of Prostatic Lesions in Multiparametric MRI].

Haas M, Günzel K, Penzkofer T, Maxeiner A, Fischer T, Miller K, Hamm B, Asbach P, Cash H. Haas M, et al. Aktuelle Urol. 2016 Sep;47(5):383-7. doi: 10.1055/s-0042-111128. Epub 2016 Sep 28. Aktuelle Urol. 2016. PMID: 27680189 German.

10

Primary magnetic resonance imaging/ultrasonography fusion-guided biopsy of the prostate.

Maxeiner A, Kittner B, Blobel C, Wiemer L, Hofbauer SL, Fischer T, Asbach P, Haas M, Penzkofer T, Fuller F, Miller K, Cash H. Maxeiner A, et al. Among authors: haas m. BJU Int. 2018 Aug;122(2):211-218. doi: 10.1111/bju.14212. Epub 2018 Apr 17. BJU Int. 2018. PMID: 29569320

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