From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge.
Péter BándiOscar GeessinkQuirine MansonMarcory Van DijkMaschenka BalkenholMeyke HermsenBabak Ehteshami BejnordiByungjae LeeKyunghyun PaengAoxiao ZhongQuanzheng LiFarhad Ghazvinian ZanjaniSvitlana ZingerKeisuke FukutaDaisuke KomuraVlado OvtcharovShenghua ChengShaoqun ZengJeppe ThagaardAnders B. DahlHuangjing LinHao ChenLudwig JacobssonMartin HedlundMelih ÇetinEren HaliciHunter JacksonRichard ChenFabian BothJörg FrankeHeidi Küsters-VandeveldeWillem VreulsPeter BultBram van GinnekenJeroen van der LaakGeert LitjensPublished in: IEEE Trans. Medical Imaging (2019)
Keyphrases
- lymph nodes
- automatic detection
- cancer diagnosis
- lung cancer
- automatic segmentation
- clinical data
- clinical practice
- decision trees
- cancer patients
- ct data
- early detection
- support vector machine svm
- ct images
- feature selection
- clinical applications
- cancer classification
- treatment planning
- feature space
- feature extraction
- breast cancer patients