title: Automatic breast cancer grading of histopathological images.
abstract: Breast cancer grading of histopathological images is the standard clinical practice for the diagnosis and prognosis of breast cancer development. In a large hospital, a pathologist typically handles 100 grading cases per day, each consisting of about 2000 image frames. It is, therefore, a very tedious and time-consuming task. This paper proposes a method for automatic computer grading to assist pathologists by providing second opinions and reducing their workload. It combines the three criteria in the Nottingham scoring system using a multi-resolution approach. To our best knowledge, there is no existing work that provide complete grading according to the Nottingham criteria.
authors.affiliation: Dept. of Computer Science, National University of Singapore, Computing 1, Singapore. jeanroma@comp.nus.edu.sg
authors.forename: Jean-Romain
authors.initials: JR
authors.lastname: Dalle
authors.forename: Wee Kheng
authors.initials: WK
authors.lastname: Leow
authors.forename: Daniel
authors.initials: D
authors.lastname: Racoceanu
authors.forename: Adina Eunice
authors.initials: AE
authors.lastname: Tutac
authors.forename: Thomas C
authors.initials: TC
authors.lastname: Putti
mesh_terms: D000465:Algorithms; D001331:Automation; D001706:Biopsy; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000473:pathology*; D002467:Cell Nucleus / Q000378:metabolism; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008495:Medical Oncology / Q000379:methods; D008938:Mitosis; D015233:Models, Statistical; D008962:Models, Theoretical; D016011:Normal Distribution; D011336:Probability; D011379:Prognosis