ScanImage: Flexible software for operating laser scanning microscopes

BACKGROUND: Laser scanning microscopy is a powerful tool for analyzing the structure and function of biological specimens. Although numerous commercial laser scanning microscopes exist, some of the more interesting and challenging applications demand custom design. A major impediment to custom design is the difficulty of building custom data acquisition hardware and writing the complex software required to run the laser scanning microscope. RESULTS: We describe a simple, software-based approach to operating a laser scanning microscope without the need for custom data acquisition hardware. Data acquisition and control of laser scanning are achieved through standard data acquisition boards. The entire burden of signal integration and image processing is placed on the CPU of the computer. We quantitate the effectiveness of our data acquisition and signal conditioning algorithm under a variety of conditions. We implement our approach in an open source software package (ScanImage) and describe its functionality. CONCLUSIONS: We present ScanImage, software to run a flexible laser scanning microscope that allows easy custom design

High-speed, long-term, 4D in vivo lifetime imaging in intact and injured zebrafish and mouse brains by instant FLIM

Traditional fluorescence microscopy is blind to molecular microenvironment information that is present in the emission decay lifetime. With fluorescence lifetime imaging microscopy (FLIM), physiological parameters such as pH, refractive index, ion concentration, dissolved gas concentration, and fluorescence resonance energy transfer (FRET) can be measured. Despite these benefits, existing FLIM techniques are typically slow, noisy, and hard to implement due to expensive instrumentation and complex post-processing. To overcome these limitations, we present instant FLIM, a method that allows real-time acquisition and display of two-photon intensity, lifetime, and phasor imaging data. Using analog signal processing, we demonstrate in vivo four-dimensional (4D) FLIM movies by imaging mouse and zebrafish glial cell response to injury over 12 hours through intact skulls. Instant FLIM can be implemented as an upgrade to an existing multiphoton microscope using cost-effective off-the-shelf components, requires no data post-processing, and is demonstrated to be compatible with FD-FLIM super-resolution techniques

Computer vision using MatLAB and the toolbox of image processing

During the implementation of computer vision algorithms the manipulation of pointers, memory administration and some other resources are expensive in time even for friendly programming language. All these problems can be resolved if the implementation test is carried out in MatLAB using its toolbox of image processing with it the time of implementation becomes the minimum with the trust of using algorithms scientifically proven and robust. In this work we show the form in which can be used matlab and its toolboxes to solve common problems of computer vision efficiently

Remote Access and Computerized User Control of Robotic Micromanipulators

Nano- and micromanipulators are critical research tools in numerous fields including micro-manufacturing and disease study. Despite their importance, nano- and micromanipulation systems remain inaccessible to many groups due to price and lack of portability. An intuitive and remotely accessible manipulation system helps mitigate this access problem. Previously, optimal control hardware for single-probe manipulation and the effect of latency on user performance were not well understood. Remote access demands full computerization; graphical user interfaces with networking capabilities were developed to fulfill this requirement and allow the use of numerous hardware controllers. Virtual environments were created to simulate the use of a manipulator with full parametric control and measurement capabilities. Users completed simulated tasks with each device and were surveyed about their perceptions. User performance with a commercial manipulator controller was exceeded by performance with both a computer mouse and pen tablet. Latency was imposed within the virtual environment to study it’s effects and establish guidelines as to which latency ranges are acceptable for long-range remote manipulation. User performance began to degrade noticeably at 100 ms and severely at 400 ms and performance with the mouse degraded the least as latency increased. A computer vision system for analyzing carbon nanotube arrays was developed so the computation time could be compared to acceptable system latency. The system characterizes the arrays to a high degree of accuracy and most of the measurement types of obtainable fast enough for real-time analysis

Strengthening of prism beam by using NSM technique with roots planted in concrete

This paper presents experimental results of four prismatic concrete reinforced beam and strengthened by NSM (Near surface mounted) FRP (Fiber Reinforced Polymer) reinforced technique, with additional roots planted in the concrete. The strengthening technique causes load capacity of beams to increase from (6%-8%).A decrease in mid-span deflection was also observed from (4%-5%).Using this technique gave increasing in flexural beam resistant under the same conditions and this increasing was also noted in shear beam resistant

Effective Smoke Detection Using Spatial-Temporal Energy and Weber Local Descriptors in Three Orthogonal Planes (WLD-TOP)

Video-based fire detection (VFD) technologies have received significant attention from both academic and industrial communities recently. However, existing VFD approaches are still susceptible to false alarms due to changes in illumination, camera noise, variability of shape, motion, colour, irregular patterns of smoke and flames, modelling and training inaccuracies. Hence, this work aimed at developing a VSD system that will have a high detection rate, low false-alarm rate and short response time. Moving blocks in video frames were segmented and analysed in HSI colour space, and wavelet energy analysis of the smoke candidate blocks was performed. In addition, Dynamic texture descriptors were obtained using Weber Local Descriptor in Three Orthogonal Planes (WLD-TOP). These features were combined and used as inputs to Support Vector Classifier with radial based kernel function, while post-processing stage employs temporal image filtering to reduce false alarm. The algorithm was implemented in MATLAB 8.1.0.604 (R2013a). Accuracy of 99.30%, detection rate of 99.28% and false alarm rate of 0.65% were obtained when tested with some online videos. The output of this work would find applications in early fire detection systems and other applications such as robot vision and automated inspection.Facultad de Informátic

Multimodal optical systems for clinical oncology

This thesis presents three multimodal optical (light-based) systems designed to improve the capabilities of existing optical modalities for cancer diagnostics and theranostics. Optical diagnostic and therapeutic modalities have seen tremendous success in improving the detection, monitoring, and treatment of cancer. For example, optical spectroscopies can accurately distinguish between healthy and diseased tissues, fluorescence imaging can light up tumours for surgical guidance, and laser systems can treat many epithelial cancers. However, despite these advances, prognoses for many cancers remain poor, positive margin rates following resection remain high, and visual inspection and palpation remain crucial for tumour detection. The synergistic combination of multiple optical modalities, as presented here, offers a promising solution. The first multimodal optical system (Chapter 3) combines Raman spectroscopic diagnostics with photodynamic therapy using a custom-built multimodal optical probe. Crucially, this system demonstrates the feasibility of nanoparticle-free theranostics, which could simplify the clinical translation of cancer theranostic systems without sacrificing diagnostic or therapeutic benefit. The second system (Chapter 4) applies computer vision to Raman spectroscopic diagnostics to achieve spatial spectroscopic diagnostics. It provides an augmented reality display of the surgical field-of-view, overlaying spatially co-registered spectroscopic diagnoses onto imaging data. This enables the translation of Raman spectroscopy from a 1D technique to a 2D diagnostic modality and overcomes the trade-off between diagnostic accuracy and field-of-view that has limited optical systems to date. The final system (Chapter 5) integrates fluorescence imaging and Raman spectroscopy for fluorescence-guided spatial spectroscopic diagnostics. This facilitates macroscopic tumour identification to guide accurate spectroscopic margin delineation, enabling the spectroscopic examination of suspicious lesions across large tissue areas. Together, these multimodal optical systems demonstrate that the integration of multiple optical modalities has potential to improve patient outcomes through enhanced tumour detection and precision-targeted therapies.Open Acces

Effective Smoke Detection Using Spatial-Temporal Energy and Weber Local Descriptors in Three Orthogonal Planes (WLD-TOP)

Video-based fire detection (VFD) technologies have received significant attention from both academic and industrial communities recently. However, existing VFD approaches are still susceptible to false alarms due to changes in illumination, camera noise, variability of shape, motion, colour, irregular patterns of smoke and flames, modelling and training inaccuracies. Hence, this work aimed at developing a VSD system that will have a high detection rate, low false-alarm rate and short response time. Moving blocks in video frames were segmented and analysed in HSI colour space, and wavelet energy analysis of the smoke candidate blocks was performed. In addition, Dynamic texture descriptors were obtained using Weber Local Descriptor in Three Orthogonal Planes (WLD-TOP). These features were combined and used as inputs to Support Vector Classifier with radial based kernel function, while post-processing stage employs temporal image filtering to reduce false alarm. The algorithm was implemented in MATLAB 8.1.0.604 (R2013a). Accuracy of 99.30%, detection rate of 99.28% and false alarm rate of 0.65% were obtained when tested with some online videos. The output of this work would find applications in early fire detection systems and other applications such as robot vision and automated inspection.Facultad de Informátic

Principal Component Analysis based Image Fusion Routine with Application to Stamping Split Detection

This dissertation presents a novel thermal and visible image fusion system with application in online automotive stamping split detection. The thermal vision system scans temperature maps of high reflective steel panels to locate abnormal temperature readings indicative of high local wrinkling pressure that causes metal splitting. The visible vision system offsets the blurring effect of thermal vision system caused by heat diffusion across the surface through conduction and heat losses to the surroundings through convection. The fusion of thermal and visible images combines two separate physical channels and provides more informative result image than the original ones. Principal Component Analysis (PCA) is employed for image fusion to transform original image to its eigenspace. By retaining the principal components with influencing eigenvalues, PCA keeps the key features in the original image and reduces noise level. Then a pixel level image fusion algorithm is developed to fuse images from the thermal and visible channels, enhance the result image from low level and increase the signal to noise ratio. Finally, an automatic split detection algorithm is designed and implemented to perform online objective automotive stamping split detection. The integrated PCA based image fusion system for stamping split detection is developed and tested on an automotive press line. It is also assessed by online thermal and visible acquisitions and illustrates performance and success. Different splits with variant shape, size and amount are detected under actual operating conditions