Structured Illumination Reflectance Imaging for Enhanced Detection of Subsurface Tissue Bruising in Apples

2018 ◽  
Vol 61 (3) ◽  
pp. 809-819 ◽  
Author(s):  
Richard Li ◽  
Yuzhen Lu ◽  
Renfu Lu
Keyword(s):  
Imaging Modality ◽  
Specific Information ◽  
Structured Illumination ◽  
Detection Rates ◽  
Detection Algorithms ◽  
Spatial Frequencies ◽  
Golden Delicious ◽  
Nondestructive Quality ◽  
Novel Method ◽  
Quality Sorting

Abstract. In this research, a structured illumination reflectance imaging (SIRI) system was used as a novel method for detection of fresh bruises on apples. The SIRI system projects sinusoidal patterns of illumination onto samples, and image demodulation is then used to recover depth-specific information through varying the spatial frequency of the illumination pattern. The capability of SIRI was demonstrated through the detection of artificially induced bruises on ‘Golden Delicious’ and ‘Delicious’ apples with varying levels of bruising. It was hypothesized that by confining the light penetration depth near the surface of each fruit, subsurface defects such as bruising should be more apparent under SIRI than conventional planar illumination imaging. Three 120° phase-shifted reflectance images were acquired from 60 fruit each of ‘Golden Delicious’ and ‘Delicious’ varieties at 0 h, 4 to 6 h, and 24 h after impact bruising for each of the four spatial frequencies (i.e., 0, 0.10, 0.15, and 0.25 cycles mm-1). The reflectance images acquired by the system were then demodulated into an alternating component (AC) and direct component (DC), where the AC contained depth-specific information and the DC image represented the diffuse reflectance from the apple sample under uniform (or planar) illumination. Bruise detection algorithms were developed and applied to the demodulated AC and DC images. The SIRI system achieved 70% to 100% bruise detection rates, compared to 0% to 50% detection rates under conventional planar illumination. However, detection results were influenced by both severity of bruising and bruise development after impact; better bruise detection results were obtained when bruises had developed for 4 to 6 h after impact. SIRI has demonstrated a superior capability of detecting fresh bruises, and it is promising as a new imaging modality for quality detection of agricultural products. Keywords: Apples, Bruises, Defects, Fruit, Imaging, Nondestructive, Quality, Sorting, Structured illumination.

scholarly journals Near Infrared Fluorescence Imaging of Intraperitoneal Ovarian Tumors in Mice Using Erythrocyte-Derived Optical Nanoparticles and Spatially-Modulated Illumination

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2544
Author(s):  
Joshua M. Burns ◽  
Elise Shafer ◽  
Raviraj Vankayala ◽  
Vikas Kundra ◽  
Bahman Anvari
Keyword(s):  
Fluorescence Imaging ◽  
Cytoreductive Surgery ◽  
Animal Studies ◽  
Near Infrared ◽  
Gynecological Cancer ◽  
Ovarian Tumors ◽  
Structured Illumination ◽  
Spatial Frequencies ◽  
Imaging Probes ◽  
Intraoperative Fluorescence Imaging

Ovarian cancer is the deadliest gynecological cancer. Cytoreductive surgery to remove primary and intraperitoneal tumor deposits remains as the standard therapeutic approach. However, lack of an intraoperative image-guided approach to enable the visualization of all tumors can result in incomplete cytoreduction and recurrence. We engineered nano-sized particles derived from erythrocytes that encapsulate the near infrared (NIR) fluorochrome, indocyanine green, as potential imaging probes for tumor visualization during cytoreductive surgery. Herein, we present the first demonstration of the use of these nanoparticles in conjunction with spatially-modulated illumination (SMI), at spatial frequencies in the range of 0–0.5 mm−1, to fluorescently image intraperitoneal ovarian tumors in mice. Results of our animal studies suggest that the nanoparticles accumulated at higher levels within tumors 24 h post-intraperitoneal injection as compared to various other organs. We demonstrate that, under the imaging specifications reported here, use of these nanoparticles in conjunction with SMI enhances the fluorescence image contrast between intraperitoneal tumors and liver, and between intraperitoneal tumors and spleen by nearly 2.1, and 3.0 times, respectively, at the spatial frequency of 0.2 mm−1 as compared to the contrast values at spatially-uniform (non-modulated) illumination. These results suggest that the combination of erythrocyte-derived NIR nanoparticles and structured illumination provides a promising approach for intraoperative fluorescence imaging of ovarian tumor nodules at enhanced contrast.

scholarly journals Double moiré localized plasmon structured illumination microscopy

Nanophotonics ◽  
2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Ruslan Röhrich ◽  
A. Femius Koenderink
Keyword(s):  
Near Field ◽  
Super Resolution ◽  
Reconstruction Algorithm ◽  
Structured Illumination ◽  
Structured Illumination Microscopy ◽  
Experimental Realization ◽  
Spatial Frequencies ◽  
Wide Range ◽  
Localized Plasmon ◽  
Plasmonic Grating

AbstractStructured illumination microscopy (SIM) is a well-established fluorescence imaging technique, which can increase spatial resolution by up to a factor of two. This article reports on a new way to extend the capabilities of structured illumination microscopy, by combining ideas from the fields of illumination engineering and nanophotonics. In this technique, plasmonic arrays of hexagonal symmetry are illuminated by two obliquely incident beams originating from a single laser. The resulting interference between the light grating and plasmonic grating creates a wide range of spatial frequencies above the microscope passband, while still preserving the spatial frequencies of regular SIM. To systematically investigate this technique and to contrast it with regular SIM and localized plasmon SIM, we implement a rigorous simulation procedure, which simulates the near-field illumination of the plasmonic grating and uses it in the subsequent forward imaging model. The inverse problem, of obtaining a super-resolution (SR) image from multiple low-resolution images, is solved using a numerical reconstruction algorithm while the obtained resolution is quantitatively assessed. The results point at the possibility of resolution enhancements beyond regular SIM, which rapidly vanishes with the height above the grating. In an initial experimental realization, the existence of the expected spatial frequencies is shown and the performance of compatible reconstruction approaches is compared. Finally, we discuss the obstacles of experimental implementations that would need to be overcome for artifact-free SR imaging.

A Novel Method for Approximating Object Location Error in Bounding Box Detection Algorithms Using a Monocular Camera

2021 ◽  
Vol 70 (9) ◽  
pp. 8682-8691
Author(s):  
Ben Miethig ◽  
Yixin Huangfu ◽  
Jiahong Dong ◽  
Jimi Tjong ◽  
Martin Von Mohrenschildt ◽  
...  
Keyword(s):  
Object Location ◽  
Location Error ◽  
Detection Algorithms ◽  
Monocular Camera ◽  
Bounding Box ◽  
Novel Method

scholarly journals Super-resolution imaging of fluorescent dipoles via polarized structured illumination microscopy

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Karl Zhanghao ◽  
Xingye Chen ◽  
Wenhui Liu ◽  
Meiqi Li ◽  
Yiqiong Liu ◽  
...  
Keyword(s):  
Hippocampal Neurons ◽  
Fluorescent Protein ◽  
Imaging Modality ◽  
Super Resolution ◽  
Vital Role ◽  
Molecular Structures ◽  
Polarization Microscopy ◽  
Structured Illumination ◽  
Structured Illumination Microscopy ◽  
Resolution Imaging

Abstract Fluorescence polarization microscopy images both the intensity and orientation of fluorescent dipoles and plays a vital role in studying molecular structures and dynamics of bio-complexes. However, current techniques remain difficult to resolve the dipole assemblies on subcellular structures and their dynamics in living cells at super-resolution level. Here we report polarized structured illumination microscopy (pSIM), which achieves super-resolution imaging of dipoles by interpreting the dipoles in spatio-angular hyperspace. We demonstrate the application of pSIM on a series of biological filamentous systems, such as cytoskeleton networks and λ-DNA, and report the dynamics of short actin sliding across a myosin-coated surface. Further, pSIM reveals the side-by-side organization of the actin ring structures in the membrane-associated periodic skeleton of hippocampal neurons and images the dipole dynamics of green fluorescent protein-labeled microtubules in live U2OS cells. pSIM applies directly to a large variety of commercial and home-built SIM systems with various imaging modality.

scholarly journals An Innovative Face Detection Based on YCgCr Color Space

2018 ◽  
Author(s):  
Solly Aryza
Keyword(s):  
Face Detection ◽  
Skin Color ◽  
Color Image ◽  
Color Space ◽  
Gaussian Model ◽  
Detection Rates ◽  
Detection Algorithms ◽  
Lighting Conditions ◽  
Wide Range ◽  
Human Faces

It is very challenging to recognize a face from an image due to the wide variety of face and the uncertain of face position. The research on detecting human faces in color image and in video sequence has been attracted with more and more people. In this paper, we propose a novel face detection method that achieves better detection rates. The new face detection algorithms based on skin color model in YCgCr chrominance space. Firstly, we build a skin Gaussian model in Cg-Cr color space. Secondly, a calculation of correlation coefficient is performed between the given template and the candidates. Experimental results demonstrate that our system has achieved high detection rates and low false positives over a wide range of facial variations in color, position and varying lighting conditions.

scholarly journals Three-Layer Data Clustering Model for Multi-View Customer Segmentation using K-Means

2020 ◽  
Vol 8 (6) ◽  
pp. 1840-1846
Keyword(s):  
Customer Relationship Management ◽  
Customer Segmentation ◽  
Customer Relationship ◽  
Specific Information ◽  
K Value ◽  
Crm System ◽  
Clustering Model ◽  
Rfm Model ◽  
Novel Method ◽  
Score Range

Customer Relationship Management (CRM) system is one of the methods to increase customer satisfaction with the services provided by the company. The data in a CRM system sometimes have not been utilized properly to find specific information about customer needs. The data mining process can help companies to segment and retrieve useful information about customers. The segmentation of customers can be categorized into groups based on the RFM (Recency, Frequency, and Monetary) values of the customers. Several studies have used the RFM model as a basis for customer segmentation. However, the methods proposed in previous studies are very specific to certain industries and the range of RFM scores used is also very subjective. Also, as the business grows there are challenges with RFM score measurement. RFM score measurement needs frequent adjustments in which this adjustment is not easy using the existing methods. Therefore, this study proposed a novel method to overcome the limitation of the existing methods using combined K-Means and Davies-Bouldin Index (DBI) to find the appropriate range of RFM scores. Based on our study in a telecommunication industry the proposed method simplify the measurement of the RMF scores as the data grows. This research also provided the appropriate RFM score range through the K-Means approach based on the optimal K value of the K-Means algorithm. Our proposed method could be implemented in other industries since it only depends on the values of RFM from the correspond data for each customer.

scholarly journals DeepTable: a permutation invariant neural network for table orientation classification

2020 ◽  
Vol 34 (6) ◽  
pp. 1963-1983
Author(s):  
Maryam Habibi ◽  
Johannes Starlinger ◽  
Ulf Leser
Keyword(s):  
Deep Neural Networks ◽  
State Of The Art ◽  
Superior Performance ◽  
Web Pages ◽  
Specific Information ◽  
Silver Standard ◽  
Present Information ◽  
Previous State ◽  
Novel Method

Abstract Tables are a common way to present information in an intuitive and concise manner. They are used extensively in media such as scientific articles or web pages. Automatically analyzing the content of tables bears special challenges. One of the most basic tasks is determination of the orientation of a table: In column tables, columns represent one entity with the different attribute values present in the different rows; row tables are vice versa, and matrix tables give information on pairs of entities. In this paper, we address the problem of classifying a given table into one of the three layouts horizontal (for row tables), vertical (for column tables), and matrix. We describe DeepTable, a novel method based on deep neural networks designed for learning from sets. Contrary to previous state-of-the-art methods, this basis makes DeepTable invariant to the permutation of rows or columns, which is a highly desirable property as in most tables the order of rows and columns does not carry specific information. We evaluate our method using a silver standard corpus of 5500 tables extracted from biomedical articles where the layout was determined heuristically. DeepTable outperforms previous methods in both precision and recall on our corpus. In a second evaluation, we manually labeled a corpus of 300 tables and were able to confirm DeepTable to reach superior performance in the table layout classification task. The codes and resources introduced here are available at https://github.com/Marhabibi/DeepTable.

Interhemispheric Integration at Different Spatial Scales: The Evidence From EEG Coherence and fMRI

2006 ◽  
Vol 96 (1) ◽  
pp. 259-275 ◽  
Author(s):  
Maria G. Knyazeva ◽  
Eleonora Fornari ◽  
Reto Meuli ◽  
Philippe Maeder
Keyword(s):  
Spatial Scales ◽  
Neural Substrates ◽  
Blood Oxygen Level Dependent ◽  
Specific Information ◽  
Eeg Coherence ◽  
Blood Oxygen Level ◽  
Spatial Frequencies ◽  
Collateral Sulcus ◽  
Gestalt Grouping ◽  
The Brain

The early visual system processes different spatial frequencies (SFs) separately. To examine where in the brain the scale-specific information is integrated, we mapped the neural assemblies engaged in interhemispheric coupling with electroencephalographic (EEG) coherence and blood-oxygen-level dependent (BOLD) signal. During similar EEG and functional magnetic resonance imaging (fMRI) experiments, our subjects viewed centrally presented bilateral gratings of different SF (0.25–8.0 cpd), which either obeyed Gestalt grouping rules (iso-oriented, IG) or violated them (orthogonally oriented, OG). The IG stimuli (0.5–4.0 cpd) synchronized EEG at discrete beta frequencies (beta1, beta2) and increased BOLD (0.5 and 2.0 cpd tested) in ventral (around collateral sulcus) and dorsal (parieto-occipital fissure) regions compared with OG. At both SF, the beta1 coherence correlated with the ventral activations, whereas the beta2 coherence correlated with the dorsal ones. Thus distributed neural substrates mediated interhemispheric integration at single SF. The relative impact of the ventral versus dorsal networks was modulated by the SF of the stimulus.

scholarly journals Sinus Venosus Atrial Septal Defect as a Cause of Palpitations and Dyspnea in an Adult: A Diagnostic Imaging Challenge

2015 ◽  
Vol 2015 ◽  
pp. 1-4 ◽  
Author(s):  
Michael S. Donovan ◽  
David Kassop ◽  
Robert A. Liotta ◽  
Edward A. Hulten
Keyword(s):  
Diagnostic Imaging ◽  
Imaging Modality ◽  
Sinus Venosus ◽  
Paroxysmal Supraventricular Tachycardia ◽  
Detection Rates ◽  
Clinical Presentations ◽  
Imaging Results ◽  
Highly Sensitive ◽  
Anomalous Pulmonary Venous Return ◽  
Exercise Induced

Sinus venosus atrial septal defects (SV-ASD) have nonspecific clinical presentations and represent a diagnostic imaging challenge. Transthoracic echocardiography (TTE) remains the initial diagnostic imaging modality. However, detection rates have been as low as 12%. Transesophageal echocardiography (TEE) improves diagnostic accuracy though it may not detect commonly associated partial anomalous pulmonary venous return (PAPVR). Cardiac magnetic resonance (CMR) imaging provides a noninvasive, highly sensitive and specific imaging modality of SV-ASD. We describe a case of an adult male with exercise-induced, paroxysmal supraventricular tachycardia who presented with palpitations and dyspnea. Despite nondiagnostic imaging results on TTE, CMR proved to be instrumental in visualizing a hemodynamically significant SV-ASD with PAPVR that ultimately led to surgical correction.

Sign in / Sign up

Export Citation Format

Share Document