16,258 research outputs found
Atlas-Based Prostate Segmentation Using an Hybrid Registration
Purpose: This paper presents the preliminary results of a semi-automatic
method for prostate segmentation of Magnetic Resonance Images (MRI) which aims
to be incorporated in a navigation system for prostate brachytherapy. Methods:
The method is based on the registration of an anatomical atlas computed from a
population of 18 MRI exams onto a patient image. An hybrid registration
framework which couples an intensity-based registration with a robust
point-matching algorithm is used for both atlas building and atlas
registration. Results: The method has been validated on the same dataset that
the one used to construct the atlas using the "leave-one-out method". Results
gives a mean error of 3.39 mm and a standard deviation of 1.95 mm with respect
to expert segmentations. Conclusions: We think that this segmentation tool may
be a very valuable help to the clinician for routine quantitative image
exploitation.Comment: International Journal of Computer Assisted Radiology and Surgery
(2008) 000-99
Registration of Standardized Histological Images in Feature Space
In this paper, we propose three novel and important methods for the
registration of histological images for 3D reconstruction. First, possible
intensity variations and nonstandardness in images are corrected by an
intensity standardization process which maps the image scale into a standard
scale where the similar intensities correspond to similar tissues meaning.
Second, 2D histological images are mapped into a feature space where continuous
variables are used as high confidence image features for accurate registration.
Third, we propose an automatic best reference slice selection algorithm that
improves reconstruction quality based on both image entropy and mean square
error of the registration process. We demonstrate that the choice of reference
slice has a significant impact on registration error, standardization, feature
space and entropy information. After 2D histological slices are registered
through an affine transformation with respect to an automatically chosen
reference, the 3D volume is reconstructed by co-registering 2D slices
elastically.Comment: SPIE Medical Imaging 2008 - submissio
Prostate Biopsy Assistance System with Gland Deformation Estimation for Enhanced Precision
Computer-assisted prostate biopsies became a very active research area during
the last years. Prostate tracking makes it possi- ble to overcome several
drawbacks of the current standard transrectal ultrasound (TRUS) biopsy
procedure, namely the insufficient targeting accuracy which may lead to a
biopsy distribution of poor quality, the very approximate knowledge about the
actual location of the sampled tissues which makes it difficult to implement
focal therapy strategies based on biopsy results, and finally the difficulty to
precisely reach non-ultrasound (US) targets stemming from different modalities,
statistical atlases or previous biopsy series. The prostate tracking systems
presented so far are limited to rigid transformation tracking. However, the
gland can get considerably deformed during the intervention because of US probe
pres- sure and patient movements. We propose to use 3D US combined with
image-based elastic registration to estimate these deformations. A fast elastic
registration algorithm that copes with the frequently occurring US shadows is
presented. A patient cohort study was performed, which yielded a statistically
significant in-vivo accuracy of 0.83+-0.54mm.Comment: This version of the paper integrates a correction concerning the
local similarity measure w.r.t. the proceedings (this typing error could not
be corrected before editing the proceedings
Medical image computing and computer-aided medical interventions applied to soft tissues. Work in progress in urology
Until recently, Computer-Aided Medical Interventions (CAMI) and Medical
Robotics have focused on rigid and non deformable anatomical structures.
Nowadays, special attention is paid to soft tissues, raising complex issues due
to their mobility and deformation. Mini-invasive digestive surgery was probably
one of the first fields where soft tissues were handled through the development
of simulators, tracking of anatomical structures and specific assistance
robots. However, other clinical domains, for instance urology, are concerned.
Indeed, laparoscopic surgery, new tumour destruction techniques (e.g. HIFU,
radiofrequency, or cryoablation), increasingly early detection of cancer, and
use of interventional and diagnostic imaging modalities, recently opened new
challenges to the urologist and scientists involved in CAMI. This resulted in
the last five years in a very significant increase of research and developments
of computer-aided urology systems. In this paper, we propose a description of
the main problems related to computer-aided diagnostic and therapy of soft
tissues and give a survey of the different types of assistance offered to the
urologist: robotization, image fusion, surgical navigation. Both research
projects and operational industrial systems are discussed
Towards ultra-high resolution 3D reconstruction of a whole rat brain from 3D-PLI data
3D reconstruction of the fiber connectivity of the rat brain at microscopic
scale enables gaining detailed insight about the complex structural
organization of the brain. We introduce a new method for registration and 3D
reconstruction of high- and ultra-high resolution (64 m and 1.3 m
pixel size) histological images of a Wistar rat brain acquired by 3D polarized
light imaging (3D-PLI). Our method exploits multi-scale and multi-modal 3D-PLI
data up to cellular resolution. We propose a new feature transform-based
similarity measure and a weighted regularization scheme for accurate and robust
non-rigid registration. To transform the 1.3 m ultra-high resolution data
to the reference blockface images a feature-based registration method followed
by a non-rigid registration is proposed. Our approach has been successfully
applied to 278 histological sections of a rat brain and the performance has
been quantitatively evaluated using manually placed landmarks by an expert.Comment: 9 pages, Accepted at 2nd International Workshop on Connectomics in
NeuroImaging (CNI), MICCAI'201
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