3D Image Capture Research Articles

Polymeric mesoporous silica nanoparticles as a pH-responsive switch to control doxorubicin intracellular delivery.

Cancer is a leading cause of death. Mesoporous nanomaterials with stimuli sensitivity have received increasing interest as efficient anti-cancer drug carriers. Here, we report hybrid mesoporous nanoparticles of PEGylated silica-poly[2-(dimethylamino)ethyl acrylate] (PEGylated MSN-g-PDMAEA) that can deliver and release the anti-cancer drug doxorubicin (DOX) to tumor cells in a pH dependent switch on/off status. The reversible pH sensitivity resulted in nanoparticles with enhanced functionality through controllable release of the anticancer drug. Confocal laser scanning microscopy (CLSM) and three dimensional (3D) image capture of the intracellular localization of nanoparticles revealed the fast and efficient drug delivery in the human hepatocellular carcinoma cell line. The results highlight the potential of these pH sensitive silica nanoparticles as a novel system for the delivery and controlled release of hydrophobic anti-cancer drugs in the treatment of solid tumors.

Computer-Aided 2D and 3D quantification of human stem cell fate from in vitro samples using Volocity high performance image analysis software

Accurate automated cell fate analysis of immunostained human stem cells from 2- and 3-dimensional (2D-3D) images would improve efficiency in the field of stem cell research. Development of an accurate and precise tool that reduces variability and the time needed for human stem cell fate analysis will improve productivity and interpretability of the data across research groups. In this study, we have created protocols for high performance image analysis software Volocity® to classify and quantify cytoplasmic and nuclear cell fate markers from 2D-3D images of human neural stem cells after in vitro differentiation. To enhance 3D image capture efficiency, we optimized the image acquisition settings of an Olympus FV10i® confocal laser scanning microscope to match our quantification protocols and improve cell fate classification. The methods developed in this study will allow for a more time efficient and accurate software based, operator validated, stem cell fate classification and quantification from 2D and 3D images, and yield the highest ≥ 94.4% correspondence with human recognized objects.

3D Imaging in Forensic Odontology

This paper describes the investigation of a new 3D capture method for acquiring and subsequent forensic analysis of bite mark injuries on human skin. When documenting bite marks with standard 2D cameras errors in photographic technique can occur if best practice is not followed. Subsequent forensic analysis of the mark is problematic when a 3D structure is recorded into a 2D space. Although strict guidelines (BAFO) exist, these are time‐consuming to follow and, due to their complexity, may produce errors. A 3D image capture and processing system might avoid the problems resulting from the 2D reduction process, simplifying the guidelines and reducing errors.Proposed Solution: a series of experiments are described in this paper to demonstrate that the potential of a 3D system might produce suitable results. The experiments tested precision and accuracy of the traditional 2D and 3D methods. A 3D image capture device minimises the amount of angular distortion, therefore such a system has the potential to create more robust forensic evidence for use in courts.A first set of experiments tested and demonstrated which method of forensic analysis creates the least amount of intra‐operator error. A second set tested and demonstrated which method of image capture creates the least amount of inter‐operator error and visual distortion. In a third set the effects of angular distortion on 2D and 3D methods of image capture were evaluated.

State-of-the-art of 3D facial reconstruction methods for face recognition based on a single 2D training image per person

3D facial reconstruction systems attempt to reconstruct 3D facial models of individuals from their 2D photographic images or video sequences. Currently published face recognition systems, which exhibit well-known deficiencies, are largely based on 2D facial images, although 3D image capture systems can better encapsulate the 3D geometry of the human face. Accordingly, face recognition research is gradually shifting from the legacy 2D domain to the more sophisticated 2D to 3D or 2D/3D hybrid domain. Currently there exist four methods for 3D facial reconstruction. These are: Stochastic Newton Optimization method (SNO) [Blanz, V., Vetter, T., 1999. A morphable model for the synthesis of 3D faces. In: Proc. 26th Annu. Conf. on Computer Graphics and Interactive Techniques, SIGGRAPH. pp. 187–194; Blanz, V., Vetter, T., 2003. Face recognition based on fitting a 3D morphable model. IEEE Trans. Pattern Anal. Machine Intell. 25(9), 1063–1074; Blanz, V., 2001. Automatische Rekonstruction der Dreidimensionalen Form von Gesichtern aus einem Einzelbild. Ph.D. Thesis, Universitat Tubingen, Germany] inverse compositional image alignment algorithm (ICIA) [Romdhani, S., Vetter, T., 2003. Efficient, robust and accurate fitting of a 3D morphable model. In: IEEE Int. Conf. on Computer Vision, vol. 2, no. 1. pp. 59–66], linear shape and texture fitting algorithm (LiST) [Romdhani, S., Blanz, V., Vetter, T., 2002. Face identification by fitting a 3D morphable model using linear shape and texture error functions. In: Proc. ECCV, vol. 4. pp. 3–19], and shape alignment and interpolation method correction (SAIMC) [Jiang, D., Hu, Y., Yan, S., Zhang, L., Zhang, H., Gao, W., 2005. Efficient 3D reconstruction for face recognition. Pattern Recogn. 38(6), 787–798]. The first three, SNO, ICIA + 3DMM, and LiST can be classified as “analysis-by-synthesis” techniques and SAIMC can be separately classified as a “3D supported 2D model”. In this paper, we introduce, discuss and analyze the difference between these two frameworks. We begin by presenting the 3D morphable model (3DMM; Blanz and Vetter, 1999), which forms the foundation of all four of the reconstruction techniques described here. This is followed by a review of the basic “analysis-by-synthesis” framework and a comparison of the three methods that employ this approach. We next review the “3D supported 2D model” framework and introduce the SAIMC method, comparing it to the other three. The characteristics of all four methods are summarized in a table that should facilitate further research on this topic.

Control and automatica trade fairs May 2006

PurposeTo report on innovations in machine vision at two important international exhibitions held in Germany in May 2006.Design/methodology/approachThe exhibitions were each visited and innovations sought and reported.FindingsMany of the innovations were in the field of 3D image capture and processing.Originality/valueAll of the reported innovations are new and will be of interest outside Germany.

Engineers and surgeons collaborate

A day conference at the Institution of Mechanical Engineers on 14 November 2000 brought together engineers engaged in development of robotic aids, and surgeons, some of whom are currently using robotic assistance in their work. The meeting provided a valuable opportunity for sharing of experience. Chairman of the event was Dr Patrick Finlay, who, as founder of Armstrong Healthcare, has been a pioneer in the development of medical robotics. Dr Finlay himself spoke about the Pathfinder image‐guided robot for neurosurgery. The aim of this is to free the surgeon and patient from the rigid stereotactic frame which has been necessary to secure the required 1mm precision of positioning for a tool tip. Mr Rory McCloy described his use of robots in laparoscopic surgery. A delicate drilling operation on flexible bone tissue in the ear was described by Professor Peter Brett, and among other presentations were three relating to 3D image capture for surgery.