2,642 research outputs found
Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery
One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeonβs navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions
Bootstrapping the Coronal Magnetic Field with STEREO: I. Unipolar Potential Field Modeling
We investigate the recently quantified misalignment of between the 3-D geometry of stereoscopically triangulated
coronal loops observed with STEREO/EUVI (in four active regions) and
theoretical (potential or nonlinear force-free) magnetic field models
extrapolated from photospheric magnetograms. We develop an efficient method of
bootstrapping the coronal magnetic field by forward-fitting a parameterized
potential field model to the STEREO-observed loops. The potential field model
consists of a number of unipolar magnetic charges that are parameterized by
decomposing a photospheric magnetogram from MDI. The forward-fitting method
yields a best-fit magnetic field model with a reduced misalignment of
. We evaluate also stereoscopic
measurement errors and find a contribution of , which constrains the residual misalignment to
, which is likely
due to the nonpotentiality of the active regions. The residual misalignment
angle of the potential field due to nonpotentiality is found to
correlate with the soft X-ray flux of the active region, which implies a
relationship between electric currents and plasma heating.Comment: 12 figures, manuscript submitted to ApJ, 2010 Apr 2
Data-Optimized Coronal Field Model: I. Proof of Concept
Deriving the strength and direction of the three-dimensional (3D) magnetic
field in the solar atmosphere is fundamental for understanding its dynamics.
Volume information on the magnetic field mostly relies on coupling 3D
reconstruction methods with photospheric and/or chromospheric surface vector
magnetic fields. Infrared coronal polarimetry could provide additional
information to better constrain magnetic field reconstructions. However,
combining such data with reconstruction methods is challenging, e.g., because
of the optical-thinness of the solar corona and the lack and limitations of
stereoscopic polarimetry. To address these issues, we introduce the
Data-Optimized Coronal Field Model (DOCFM) framework, a model-data fitting
approach that combines a parametrized 3D generative model, e.g., a magnetic
field extrapolation or a magnetohydrodynamic model, with forward modeling of
coronal data. We test it with a parametrized flux rope insertion method and
infrared coronal polarimetry where synthetic observations are created from a
known "ground truth" physical state. We show that this framework allows us to
accurately retrieve the ground truth 3D magnetic field of a set of force-free
field solutions from the flux rope insertion method. In observational studies,
the DOCFM will provide a means to force the solutions derived with different
reconstruction methods to satisfy additional, common, coronal constraints. The
DOCFM framework therefore opens new perspectives for the exploitation of
coronal polarimetry in magnetic field reconstructions and for developing new
techniques to more reliably infer the 3D magnetic fields that trigger solar
flares and coronal mass ejections.Comment: 14 pages, 6 figures; Accepted for publication in Ap
Airborne photogrammetry and LIDAR for DSM extraction and 3D change detection over an urban area : a comparative study
A digital surface model (DSM) extracted from stereoscopic aerial images, acquired in March 2000, is compared with a DSM derived from airborne light detection and ranging (lidar) data collected in July 2009. Three densely built-up study areas in the city centre of Ghent, Belgium, are selected, each covering approximately 0.4 km(2). The surface models, generated from the two different 3D acquisition methods, are compared qualitatively and quantitatively as to what extent they are suitable in modelling an urban environment, in particular for the 3D reconstruction of buildings. Then the data sets, which are acquired at two different epochs t(1) and t(2), are investigated as to what extent 3D (building) changes can be detected and modelled over the time interval. A difference model, generated by pixel-wise subtracting of both DSMs, indicates changes in elevation. Filters are proposed to differentiate 'real' building changes from false alarms provoked by model noise, outliers, vegetation, etc. A final 3D building change model maps all destructed and newly constructed buildings within the time interval t(2) - t(1). Based on the change model, the surface and volume of the building changes can be quantified
Visualization and Correction of Automated Segmentation, Tracking and Lineaging from 5-D Stem Cell Image Sequences
Results: We present an application that enables the quantitative analysis of
multichannel 5-D (x, y, z, t, channel) and large montage confocal fluorescence
microscopy images. The image sequences show stem cells together with blood
vessels, enabling quantification of the dynamic behaviors of stem cells in
relation to their vascular niche, with applications in developmental and cancer
biology. Our application automatically segments, tracks, and lineages the image
sequence data and then allows the user to view and edit the results of
automated algorithms in a stereoscopic 3-D window while simultaneously viewing
the stem cell lineage tree in a 2-D window. Using the GPU to store and render
the image sequence data enables a hybrid computational approach. An
inference-based approach utilizing user-provided edits to automatically correct
related mistakes executes interactively on the system CPU while the GPU handles
3-D visualization tasks. Conclusions: By exploiting commodity computer gaming
hardware, we have developed an application that can be run in the laboratory to
facilitate rapid iteration through biological experiments. There is a pressing
need for visualization and analysis tools for 5-D live cell image data. We
combine accurate unsupervised processes with an intuitive visualization of the
results. Our validation interface allows for each data set to be corrected to
100% accuracy, ensuring that downstream data analysis is accurate and
verifiable. Our tool is the first to combine all of these aspects, leveraging
the synergies obtained by utilizing validation information from stereo
visualization to improve the low level image processing tasks.Comment: BioVis 2014 conferenc
ΠΠ΅ΡΠΊΠΎΠ½ΡΠ°ΠΊΡΠ½ΡΠΉ ΠΌΠΎΠ½ΠΈΡΠΎΡΠΈΠ½Π³ Π΄ΡΡ Π°Π½ΠΈΡ Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΠΎΠΏΡΠΈΡΠ΅ΡΠΊΠΈΡ Π΄Π°ΡΡΠΈΠΊΠΎΠ²
Π¦ΡΠ»Π»Ρ Π΄Π°Π½ΠΎΡ ΡΠΎΠ±ΠΎΡΠΈ Ρ ΠΊΠ»Π°ΡΠΈΡΡΠΊΠ°ΡΡΡ ΠΏΡΠ΄Ρ
ΠΎΠ΄ΡΠ² Π΄ΠΎ Π±Π΅Π·ΠΊΠΎΠ½ΡΠ°ΠΊΡΠ½ΠΎΠ³ΠΎ ΠΌΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³Ρ Π΄ΠΈΡ
Π°Π½Π½Ρ Ρ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠ° ΡΡΡΡΠΊΡΡΡΠΈ ΡΠΈΡΡΠ΅ΠΌΠΈ ΠΌΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³Ρ Π· ΡΡΡΠ½Π΅Π½Π½ΡΠΌ Π°ΡΡΠ΅ΡΠ°ΠΊΡΡΠ² ΠΌΡΠΌΡΠΊΠΈ. Π£ΡΡ Π½Π°ΡΠ²Π½Ρ ΠΌΠ΅ΡΠΎΠ΄ΠΈ Π±ΡΠ»ΠΈ ΡΠΎΠ·Π΄ΡΠ»Π΅Π½Ρ Π½Π° Π΄Π²Ρ ΠΎΡΠ½ΠΎΠ²Π½Ρ Π³ΡΡΠΏΠΈ: ΠΌΠ΅ΡΠΎΠ΄ΠΈ Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ Π²ΠΈΠ·Π½Π°ΡΠ΅Π½Π½Ρ Π΄ΠΈΡ
Π°Π½Π½Ρ Π· 3-D Π·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½Π½Ρ ΠΎΠ±'ΡΠΊΡΠ° Ρ ΠΌΠ΅ΡΠΎΠ΄ΠΈ Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ 2-D ΠΎΠ±ΡΠΎΠ±ΠΊΠΈ Π·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½Ρ. ΠΡΠ»Π° ΡΠΎΠ·ΡΠΎΠ±Π»Π΅Π½Π° ΡΡΡΡΠΊΡΡΡΠ° ΡΠΈΡΡΠ΅ΠΌΠΈ ΠΌΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³Ρ Π΄ΠΈΡ
Π°Π½Π½Ρ Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ ΠΎΠΏΡΠΈΡΠ½ΠΈΡ
ΡΠ΅Π½ΡΠΎΡΡΠ² Π· ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π²ΠΈΠ΄Π°Π»Π΅Π½Π½Ρ Π°ΡΡΠ΅ΡΠ°ΠΊΡΡΠ² ΠΌΡΠΌΡΠΊΠΈ. ΠΠΎΠ²ΠΈΠΉ ΠΏΡΠ΄Ρ
ΡΠ΄ Π΄ΠΎΠ·Π²ΠΎΠ»ΡΡ ΠΏΠΎΠΊΡΠ°ΡΠΈΡΠΈ ΠΌΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³ Π΄ΠΈΡ
Π°Π½Π½Ρ Π΄Π»Ρ ΠΎΠ±'ΡΠΊΡΡΠ² Π² ΠΏΠΎΠ»ΠΎΠΆΠ΅Π½Π½Ρ Π»Π΅ΠΆΠ°ΡΠΈ Π½Π° ΡΠΏΠΈΠ½Ρ Ρ Π² ΠΏΠΎΠ·ΠΈΡΡΡ ΡΠΈΠ΄ΡΡΠΈ.The main goal of this paper is to develop classification of non-contact respiration monitoring approaches and proposal of structure for system with facial artifacts rejection. All available techniques were divided into two main groups: based on reconstruction of respiration from 3-D image of object and based on 2-D image processing of techniques. Structure of system for respiration monitoring using optical sensors with facial artifacts removing was developed. New approach allows improving of respiration monitoring for objects in supine position and in a sitting position.Π¦Π΅Π»ΡΡ ΡΠ°Π±ΠΎΡΡ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΡ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ΠΎΠ² ΠΊ Π±Π΅ΡΠΊΠΎΠ½ΡΠ°ΠΊΡΠ½ΠΎΠΌΡ ΠΌΠΎΠ½ΠΈΡΠΎΡΠΈΠ½Π³Ρ Π΄ΡΡ
Π°Π½ΠΈΡ ΠΈ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ° ΡΡΡΡΠΊΡΡΡΡ ΡΠΈΡΡΠ΅ΠΌΡ ΠΌΠΎΠ½ΠΈΡΠΎΡΠΈΠ½Π³Π° Ρ ΡΡΡΡΠ°Π½Π΅Π½ΠΈΠ΅ΠΌ Π°ΡΡΠ΅ΡΠ°ΠΊΡΠΎΠ² ΠΌΠΈΠΌΠΈΠΊΠΈ. ΠΡΠ΅ ΠΈΠΌΠ΅ΡΡΠΈΠ΅ΡΡ ΠΌΠ΅ΡΠΎΠ΄Ρ Π±ΡΠ»ΠΈ ΡΠ°Π·Π΄Π΅Π»Π΅Π½Ρ Π½Π° Π΄Π²Π΅ ΠΎΡΠ½ΠΎΠ²Π½ΡΠ΅ Π³ΡΡΠΏΠΏΡ: ΠΌΠ΅ΡΠΎΠ΄Ρ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ Π΄ΡΡ
Π°Π½ΠΈΡ ΠΈΠ· 3-D ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΡ ΠΎΠ±ΡΠ΅ΠΊΡΠ° ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ 2-D ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΠΉ. ΠΡΠ»Π° ΡΠ°Π·ΡΠ°Π±ΠΎΡΠ°Π½Π° ΡΡΡΡΠΊΡΡΡΠ° ΡΠΈΡΡΠ΅ΠΌΡ ΠΌΠΎΠ½ΠΈΡΠΎΡΠΈΠ½Π³Π° Π΄ΡΡ
Π°Π½ΠΈΡ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΎΠΏΡΠΈΡΠ΅ΡΠΊΠΈΡ
Π΄Π°ΡΡΠΈΠΊΠΎΠ² Ρ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡΡ ΡΠ΄Π°Π»Π΅Π½ΠΈΡ Π°ΡΡΠ΅ΡΠ°ΠΊΡΠΎΠ² ΠΌΠΈΠΌΠΈΠΊΠΈ. ΠΠΎΠ²ΡΠΉ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΡΠ»ΡΡΡΠΈΡΡ ΠΌΠΎΠ½ΠΈΡΠΎΡΠΈΠ½Π³ Π΄ΡΡ
Π°Π½ΠΈΡ Π΄Π»Ρ ΠΎΠ±ΡΠ΅ΠΊΡΠΎΠ² Π² ΠΏΠΎΠ»ΠΎΠΆΠ΅Π½ΠΈΠΈ Π»Π΅ΠΆΠ° Π½Π° ΡΠΏΠΈΠ½Π΅ ΠΈ Π² ΠΏΠΎΠ·ΠΈΡΠΈΠΈ ΡΠΈΠ΄Ρ
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