DVOŘÁK, J., et al. Volume estimation from single images: an application to pancreatic islets. Image Analysis and Stereology. 2018, 37(3), 191-204. ISSN 1580-3139. DOI 10.5566/ias.1869.
The present paper deals with the problem of volume estimation of individual objects from a single 2D view.
Our main application is volume estimation of pancreatic (Langerhans) islets and the single 2D view constraint
comes from the time and equipment limitations of the standard clinical procedure.
Two main approaches are followed in this paper. First, two regression-based methods are proposed, using
a set of simple shape descriptors of the segmented image of the islet. Second, two example-based methods are
proposed, based on a database of islets with known volume. For training and evaluation, islet volumes were
determined by OPT microscopy and a stereological volume estimation using the so-called Fakir probes.
The performance of the single image volume estimation methods is studied on a set of 99 islets from human
donors. Further experiments were also performed on a stone dataset and on synthetic 3D shapes, generated
using a flexible stochastic particle model. The proposed methods are fast and the experimental results show
that in most situations the proposed methods perform significantly better than the methods currently used in
clinical practice, which are based on simple spherical or ellipsoidal models.
info:eu-repo/grantAgreement/Czech Science Foundation/GA/GA17-15361S/CZ/Learning local concepts from global training data for biomedical image segmentation and classification/
dc.relation.projectid
info:eu-repo/grantAgreement/EC/OPVVV/CZ.02.1.01%2F0.0%2F0.0%2F16_019%2F0000765/CZ/Research Center for Informatics/-