title: Automated lymph node detection and classification on breast and prostate cancer SPECT-CT images.
abstract: We present a novel detection and classification method to process SPECT-CT images representing breast and prostate lymph nodes. Lymph nodes are those nodes that are near the primer tumor and may become cancerous in time, hence their early detection is a key factor for the successful treatment of the patient. Prior methods focus on the visual aid to manually detect the lymph nodes which still makes the process time-consuming. Other solutions segment the lymph nodes only on CT, where the small lymph nodes may not be located accurately. Our solution processed both SPECT and CT data to provide an accurate classification of all SPECT hot spots. The method has been validated on a huge amount of medical data. Results show that our method is a very effective tool to support physicians working with related images in the field of nuclear medicine.
authors.affiliation: Mediso Medical Imaging Systems Ltd, Baross str 91-95, Budapest, Hungary.
authors.forename: Laszlo
authors.initials: L
authors.lastname: Papp
authors.forename: Norbert
authors.initials: N
authors.lastname: Zsoter
authors.forename: Charlotte
authors.initials: C
authors.lastname: Loh
authors.forename: Baeumer
authors.initials: B
authors.lastname: Ole
authors.forename: Bernhard
authors.initials: B
authors.lastname: Egeler
authors.forename: Ildiko
authors.initials: I
authors.lastname: Garai
authors.forename: Ulf
authors.initials: U
authors.lastname: Luetzen
mesh_terms: D001331:Automation; D001943:Breast Neoplasms / Q000473:pathology*; D005260:Female; D006801:Humans; D008207:Lymphatic Metastasis / Q000175:diagnosis*; D008297:Male; D011471:Prostatic Neoplasms / Q000473:pathology*; D015899:Tomography, Emission-Computed, Single-Photon / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods*