TH-PS2c: Classification in Histology and Cytology

Session Type: Poster
Time: Thursday, March 31, 08:15 - 09:50
Location: CC11A-B
 
TH-PS2c.1: COMPARISON OF SPARSE CODING AND KERNEL METHODS FOR HISTOPATHOLOGICAL CLASSIFICATION OF GLIOBASTOMA MULTIFORME
         Ju Han; Lawrence Berkeley National Laboratory
         Hang Chang; Lawrence Berkeley National Laboratory
         Leandro Loss; LBNL
         Kai Zhang; LBNL
         Fredrick L. Baehner; Lawrence Berkeley National Laboratory
         Joe Gray; Lawrence Berkeley National Laboratory
         Paul Spellman; Lawrence Berkeley National Laboratory
         Bahram Parvin; Lawrence Berkeley National Laboratory
 
TH-PS2c.2: CASCADED MULTI-CLASS PAIRWISE CLASSIFIER (CASCAMPA) FOR NORMAL, CANCEROUS, AND CANCER CONFOUNDER CLASSES IN PROSTATE HISTOLOGY
         Scott Doyle; Rutgers University
         Michael Feldman; University of Pennsylvania
         John Tomaszewski; University of Pennsylvania
         Natalie Shih; University of Pennsylvania
         Anant Madabhushi; Rutgers University
 
TH-PS2c.3: FAST CELL DETECTION IN HIGH-THROUGHPUT IMAGERY USING GPU-ACCELERATED MACHINE LEARNING
         David Mayerich; University of Illinois, Urbana-Champaign
         Jaerock Kwon; Kettering University
         Aaron Panchal; Westmont College
         John Keyser; Texas A&M University
         Yoonsuck Choe; Texas A&M University
 
TH-PS2c.4: STATISTICAL COLOR TEXTURE DESCRIPTORS FOR HISTOLOGICAL IMAGES ANALYSIS
         Nicolas Herve; Institut Pasteur
         Aude Servais; Necker Hospital
         Eric Thervet; Necker Hospital
         Jean-Christophe Olivo-Marin; Institut Pasteur
         Vannary Meas-Yedid; Institut Pasteur
 
TH-PS2c.5: SPHERICAL BESSEL FILTER FOR 3D OBJECT DETECTION
         Henrik Skibbe; University of Freiburg
         Marco Reisert; University Medical Center Freiburg
         Olaf Ronneberger; University of Freiburg
         Hans Burkhardt; University of Freiburg
 
TH-PS2c.6: OUT-OF-SAMPLE EXTRAPOLATION USING SEMI-SUPERVISED MANIFOLD LEARNING (OSE-SSL): CONTENT-BASED IMAGE RETRIEVAL FOR PROSTATE HISTOLOGY GRADING
         Rachel Sparks; Rutgers University
         Anant Madabhushi; Rutgers University