Bone segmentation in contrast enhanced whole-body computed tomography

Segmentation of bone regions allows for enhanced diagnostics, disease characterisation and treatment monitoring in CT imaging. In contrast enhanced whole-body scans accurate automatic segmentation is particularly difficult as low dose whole body protocols reduce image quality and make contrast enhanced regions more difficult to separate when relying on differences in pixel intensities. This paper outlines a U-net architecture with novel preprocessing techniques, based on the windowing of training data and the modification of sigmoid activation threshold selection to successfully segment bone-bone marrow regions from low dose contrast enhanced whole-body CT scans. The proposed method achieved mean Dice coefficients of 0.979 ±0.02, 0.965 ±0.03, and 0.934 ±0.06 on two internal datasets and one external test dataset respectively. We have demonstrated that appropriate preprocessing is important for differentiating between bone and contrast dye, and that excellent results can be achieved with limited data.

Microscope-AOtools: A generalised adaptive optics implementation

Microscope-AOtools is a software package which allows for a simple, robust and generalised implementation of adaptive optics (AO) elements. It contains all the necessary methods for set-up, calibration, and aberration correction which are simple to use and function in a robust manner. Aberrations arising from sources such as sample hetero-geneity and refractive index mismatches are constant problems in biological imaging. These aberrations reduce image quality and the achievable depth of imaging, particularly in super-resolution microscopy techniques. AO technology has been proven to be effective in correcting for these aberrations and thereby improving the image quality. However, it has not been widely adopted by the biological imaging community due, in part, to difficulty in set-up and operation of AO, particularly by non-specialist users. Microscope-AOtools offers a robust, easy-to-use implementation of the essential methods for set-up and use of AO techniques. These methods are constructed in a generalised manner that can utilise a range of adaptive optics elements, wavefront sensing techniques and sensorless AO correction methods. Furthermore, the methods are designed to be easily extensible as new techniques arise, leading to a streamlined pipeline for new AO technology and techniques to be adopted by the wider microscopy community.

Implementasi Jaringan Saraf Tiruan Sebagai Alat Bantu Deteksi Bakteri Staphylococcus Aureus Pada Sayuran

This study aims to aid bacterial detection through bacterial imagery in vegetables to help identify Staphylococcus aureus bacteria in vegetables. Input to the software is the image of bacteria in vegetables. Bacterial image is processed by grayscaling, thresholding and image segmentation processing methods so that the image characteristics that represent bacteria in vegetables are obtained. One technique that can be used as a tool to observe Staphylococcus aureus is to use artificial neural networks and combine them with image processing. Artificial neural networks function as information processing by inferring information from data that has been received and as a decision maker for data that has been studied. Image processing is the science of manipulating images, which includes techniques to improve or reduce image quality. The detection process using software that has been built can be done well. The process is carried out by matching the value of the exercise cutra backpropagation vector with the image to be detected.

Parameter Estimation and Error Calibration for Multi-Channel Beam-Steering SAR Systems

Multi-channel beam-steering synthetic aperture radar (multi-channel BS-SAR) can achieve high resolution and wide-swath observations by combining beam-steering technology and azimuth multi-channel technology. Various imaging algorithms have been proposed for multi-channel BS-SAR but the associated parameter estimation and error calibration have received little attention. This paper focuses on errors in the main parameters in multi-channel BS-SAR (the derotation rate and constant Doppler centroid) and phase inconsistency errors. These errors can significantly reduce image quality by causing coarser resolution, radiometric degradation, and appearance of ghost targets. Accurate derotation rate estimation is important to remove the spectrum aliasing caused by beam steering, and spectrum reconstruction for multi-channel sampling requires an accurate estimate of the constant Doppler centroid and phase inconsistency errors. The time shift and scaling effect of the derotation error on the azimuth spectrum are analyzed in this paper. A method to estimate the derotation rate is presented, based on time shifting, and integrated with estimation of the constant Doppler centroid. Since the Doppler histories of azimuth targets are space-variant in multi-channel BS-SAR, the conventional estimation methods of phase inconsistency errors do not work, and we present a novel method based on minimum entropy to estimate and correct these errors. Simulations validate the proposed error estimation methods.

Active head motion reduction in Magnetic Resonance Imaging using tactile feedback

Head motion is a common problem in clinical as well as empirical (functional) Magnetic Resonance Imaging applications, as it can lead to severe artefacts that reduce image quality. The scanned individuals themselves, however, are often not aware of their head motion. The current study explored whether providing subjects with this information using tactile feedback would reduce their head motion and consequently improve image quality. In a single session that included six runs, 24 participants performed three different cognitive tasks: (1) passive viewing, (2) mental imagery, and (3) speeded responses. These tasks occurred in two different conditions: (a) with a strip of medical tape applied from one side of the MR head-coil, via the participant’s forehead, to the other side, and (b) without the medical tape being applied. Results revealed that application of medical tape to the forehead of subjects to provide tactile feedback significantly reduced both translational as well as rotational head motion. While this effect did not differ between the three cognitive tasks, there was a negative quadratic relationship between head motion with and without feedback. That is, the more head motion a subject produced without feedback, the stronger the motion reduction given the feedback. In conclusion, the here tested method provides a simple and cost-efficient way to reduce subjects’ head motion, and might be especially beneficial when extensive head motion is expected a priori.

Cryo-SOFI enabling low-dose super-resolution correlative light and electron cryo-microscopy

Correlative light and electron cryo-microscopy (cryo-CLEM) combines information from the specific labeling of fluorescence cryo-microscopy (cryo-FM) with the high resolution in environmental context of electron cryo-microscopy (cryo-EM). Exploiting super-resolution methods for cryo-FM is advantageous, as it enables the identification of rare events within the environmental background of cryo-EM at a sensitivity and resolution beyond that of conventional methods. However, due to the need for relatively high laser intensities, current super-resolution cryo-CLEM methods require cryo-protectants or support films which can severely reduce image quality in cryo-EM and are not compatible with many samples, such as mammalian cells. Here, we introduce cryogenic super-resolution optical fluctuation imaging (cryo-SOFI), a low-dose super-resolution imaging scheme based on the SOFI principle. As cryo-SOFI does not require special sample preparation, it is fully compatible with conventional cryo-EM specimens, and importantly, it does not affect the quality of cryo-EM imaging. By applying cryo-SOFI to a variety of biological application examples, we demonstrate resolutions up to ∼135 nm, an improvement of up to three times compared with conventional cryo-FM, while maintaining the specimen in a vitrified state for subsequent cryo-EM. Cryo-SOFI presents a general solution to the problem of specimen devitrification in super-resolution cryo-CLEM. It does not require a complex optical setup and can easily be implemented in any existing cryo-FM system.

A Survey of Various Image De-noising Techniques

The image processing is the technology through which information of image get processed . the noises are the extra pixels which get added on the image to reduce image quality. The authors proposed various techniques which works to remove noisy pixels from the image. In this paper, various image de-nosing techniques has been reviewed and discuss in terms of their outcomes.

Pixel Analysis Technique for Image Denoising

The image de-noising is the technique which is applied to de-noise the image. The noise is the extra pixels which are added on the image to reduce image quality. In the previous times, various techniques have been proposed which remove noisy pixels from the image. In the base paper, technique of sparse matrix technique proposed which divide the whole image into small matrixes and similarity of each matrix is calculated. The matrix which is maximum dissimilarity is removed from the image. This leads to remove noisy pixels from the image and increase image quality in terms of various parameters. In this work, technique of probability is proposed which calculate probability of each pixel and pixels which has maximum probability to be noisy is remove the image. The proposed technique is implemented in MATLAB and compare with existing technique of sparse matrix. It is been analyzed that proposed technique performs well in terms of various matrix.