Comparison of automated segmentation techniques for magnetic resonance images of the prostate

BMC Medical Imaging

Research

Francesco Alessandro Mistretta¹  Ottavio De Cobelli¹  Stefano Luzzago¹  Gennaro Musi¹  Giuseppe Petralia²  Mattia Zaffaroni³  Giulia Corrao³  Matteo Pepa³  Maria Giulia Vincini³  Lars Johannes Isaksson³  Giovanni Carlo Mazzola⁴  Stefania Volpe⁴  Giulia Marvaso⁴  Barbara Alicja Jereczek-Fossa⁴  Marco Rotondi⁴  Paul Summers⁵  Sarah Alessi⁵  Paola Pricolo⁵  Federica Cattani⁶  Giuliana Lo Presti⁷  Sara Gandini⁷  Sara Raimondi⁷  Marta Cremonesi⁸  Zaharudin Haron⁹  Roberto Orecchia^1,10 

[1] Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy;Division of Urology, IEO European Institute of Oncology IRCCS, Milan, Italy;Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy;Precision Imaging and Research Unit, Department of Medical Imaging and Radiation Sciences, IEO European Institute of Oncology IRCCS, Milan, Italy;Department of Radiation Oncology, IEO European Institute of Oncology IRCCS, Milan, Italy;Department of Radiation Oncology, IEO European Institute of Oncology IRCCS, Milan, Italy;Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy;Division of Radiology, IEO European Institute of Oncology IRCCS, Milan, Italy;Medical Physics Unit, IEO European Institute of Oncology IRCCS, Milan, Italy;Molecular and Pharmaco-Epidemiology Unit, Department of Experimental Oncology, IEO European Institute of Oncology IRCCS, Milan, Italy;Radiation Research Unit, IEO European Institute of Oncology IRCCS, Milan, Italy;Radiology Department, National Cancer Institute, Putrajaya, Malaysia;Scientific Direction, IEO European Institute of Oncology IRCCS, Milan, Italy;

关键词: Segmentation;    Prostate;    MRI;    Deep learning;    Medical image;   

DOI  :  10.1186/s12880-023-00974-y

 received in 2022-09-06, accepted in 2023-01-20,  发布年份 2023

来源: Springer

【 授权许可】

CC BY   
© The Author(s) 2023

【 图 表 】

Fig. 8

Fig. 2

Fig. 1

Fig. 3

Fig. 6

Fig. 4

Fig. 1

Fig. 7

Fig. 3

Fig. 3

Fig. 3

Fig. 2

Fig. 2

Fig. 4

Fig. 1

Fig. 6

12936_2023_4483_Article_IEq20.gif

Fig. 5

Fig. 1

Fig. 1

Fig. 7

12936_2023_4483_Article_IEq15.gif

Fig. 2

12936_2023_4483_Article_IEq13.gif

Fig. 5

Fig. 2

12936_2023_4483_Article_IEq25.gif

Fig. 3

Fig. 1

Fig. 2

40854_2022_391_Article_IEq6.gif

Fig. 3

Fig. 2

Fig. 2

Fig. 1

Fig. 2

Fig. 7

Fig. 1

40854_2023_458_Article_IEq165.gif

Fig. 1

Fig. 9

Fig. 4

Fig. 3

Fig. 1

Fig. 3

Fig. 8

12938_2023_1070_Article_IEq26.gif

Fig. 7

Fig. 1

Fig. 2

Fig.6

Fig. 7

Fig. 4

12938_2023_1070_Article_IEq19.gif

Fig.5

Fig. 5

Fig. 1

Fig. 4

Fig. 5

40854_2023_458_Article_IEq156.gif

Fig. 5

Fig. 3

Fig. 4

Fig. 4

Fig. 2

Fig. 3

40854_2023_458_Article_IEq152.gif

Fig. 3

Fig. 4

Fig. 2

Fig. 1

Fig. 1

Fig. 1

Fig. 3

Fig. 1

12938_2023_1070_Article_IEq90.gif

Fig.2

Fig. 2

Fig. 4

Fig. 4

Fig. 2

Fig. 3

Fig. 2

Fig. 6

Fig. 1

Fig. 3

Fig. 10

Fig. 4

Fig. 2

13731_2023_266_Article_IEq33.gif

Fig. 3

Fig. 5

Fig. 1

Fig. 3

13731_2023_266_Article_IEq9.gif

Fig. 1

Fig. 2

Fig. 4

Fig. 3

Fig. 2