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A Method of Segmenting Apples Based on Gray-Centered RGB Color Space

REMOTE SENSING 2021年第6期13卷 1211-1211页

作者： Fan, Pan Lang, Guodong Yan, Bin Lei, Xiaoyan Guo, Pengju Liu, Zhijie Yang, Fuzeng Northwest A&F Univ Coll Mech & Elect Engn Yangling 712100 Shaanxi Peoples R China Baoji Univ Arts & Sci Sch Comp Sci & Technol Baoji 721016 Peoples R China Shannxi Key Lab Apple Yangling 712100 Shaanxi Peoples R China Apple Mech Res Base Yangling 712100 Shaanxi Peoples R China State Key Lab Soil Eros & Dryland Farming Loess P Yangling 712100 Shaanxi Peoples R China

In recent years, many agriculture-related problems have been evaluated with the integration of artificial intelligence techniques and remote sensing systems. The rapid and accurate identification of apple targets in an illuminated and unstructured natural orchard is still a key challenge for the picking robot's vision system. In this paper, by combining local image features and color information, we propose a pixel patch segmentation method based on gray-centered red-green-blue (RGB) color space to address this issue. Different from the existing methods, this method presents a novel color feature selection method that accounts for the influence of illumination and shadow in apple images. By exploring both color features and local variation in apple images, the proposed method could effectively distinguish the apple fruit pixels from other pixels. Compared with the classical segmentation methods and conventional clustering algorithms as well as the popular deep-learning segmentation algorithms, the proposed method can segment apple images more accurately and effectively. The proposed method was tested on 180 apple images. It offered an average accuracy rate of 99.26%, recall rate of 98.69%, false positive rate of 0.06%, and false negative rate of 1.44%. Experimental results demonstrate the outstanding performance of the proposed method.

关键词： fruit detection fruit segmentation color space segmentation algorithm

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A Novel Fusion Approach to Detect Brain Tumor Using Machine Learning for MRI Images

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TRAITEMENT DU SIGNAL 2022年第4期39卷 1363-1370页

作者： Kaliannan, Srisabarimani Rengaraj, Arthi Daniel, Alex Prabhu SRM Inst Sci & Technol ECE Ramapuram Chennai 600089 Tamil Nadu India Chettinad Hosp & Res Inst Chennai 603103 Tamil Nadu India

Medical Imaging challenges the recent researchers with variability of potential structures, positions and appearance strengths of various tumors present among the patients. The proposed work presents an effective brain tumor watershed segmentation technique created on 2D image followed by statistical feature extraction. Machine Learning models such as SVM, KNN, and XG boost were used to inspire the network design in order to extract tumor existence. The proposed segmentation algorithm has been tested and evaluated on original images that consist of an aggregate of 52 normal MRI volumes of distinctive patients with the presence of tumors or not signifying distinctive structures that obtains outcomes near to physical segmentation implementations. The novelty present in the proposed work classifies whether the tumor is present or not with an accuracy of approximately 98%.

关键词： brain tumor segmentation algorithm XG boost algorithm machine learning

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Elastic founder graphs improved and enhanced

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THEORETICAL COMPUTER SCIENCE 2024年 982卷

作者： Rizzo, Nicola Equi, Massimo Norri, Tuukka Maekinen, Veli Univ Helsinki Dept Comp Sci Helsinki Finland

Indexing labeled graphs for pattern matching is a central challenge of pangenomics. Equi et al. (2022) [14] developed the Elastic Founder Graph (EFG) representing an alignment of m sequences of length n, drawn from alphabet Sigma plus the special gap character: the paths spell the original sequences or their recombination. By enforcing the semi-repeat-free property, the EFG admits a polynomial-space index for linear-time pattern matching, breaking through the conditional lower bounds on indexing labeled graphs (Equi et al. [13]). In this work, we improve the space of the EFG index answering pattern matching queries in linear time, from linear in the length of all strings spelled by three consecutive node labels, to linear in the size of the edge labels. Then, we develop linear-time construction algorithms optimizing for different metrics: we improve the existing linearithmic construction algorithms to O(mn), by solving the novel exclusive ancestor set problem on trees;we propose, for the simplified gapless setting, an O(mn)-time solution minimizing the maximum block height, that we generalize by substituting block height with prefix-aware height. Finally, to show the versatility of the framework, we develop a BWT-based EFG index and study how to encode and perform document listing queries on a set of paths of the graphs, reporting which paths present a given pattern as a substring. We propose the EFG framework as an improved and enhanced version of the framework for the gapless setting, along with construction methods that are valid in any setting concerned with the segmentation of aligned sequences.

关键词： Multiple sequence alignment Pattern matching segmentation algorithm Suffix tree Document listing

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Thermoplastic 3D printing technology using a single filament for producing realistic patient-derived breast models

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PHYSICS IN MEDICINE AND BIOLOGY 2022年第4期67卷 045008-045008页

作者： Dukov, Nikolay Bliznakova, Kristina Okkalidis, Nikiforos Teneva, Tsvetelina Encheva, Elitsa Bliznakov, Zhivko Med Univ Varna Dept Med Equipment Elect & Informat Technol Healt Varna Bulgaria Morphe Thessaloniki Greece Med Univ Varna Dept Imaging Diagnost Intervent Radiol & Radiothe Varna Bulgaria

Objective. This work describes an approach for producing physical anthropomorphic breast phantoms from clinical patient data using three-dimensional (3D) fused-deposition modelling (FDM) printing. Approach. The source of the anthropomorphic model was a clinical Magnetic Resonance Imaging (MRI) patient image set, which was segmented slice by slice into adipose and glandular tissues, skin and tumour formations;thus obtaining a four component computational breast model. The segmented tissues were mapped to specific Hounsfield Units (HU) values, which were derived from clinical breast Computed Tomography (CT) data. The obtained computational model was used as a template for producing a physical anthropomorphic breast phantom using 3D printing. FDM technology with only one polylactic acid filament was used. The physical breast phantom was scanned at Siemens SOMATOM Definition CT. Quantitative and qualitative evaluation were carried out to assess the clinical realism of CT slices of the physical breast phantom. Main results. The comparison between selected slices from the computational breast phantom and CT slices of the physical breast phantom shows similar visual x-ray appearance of the four breast tissue structures: adipose, glandular, tumour and skin. The results from the task-based evaluation, which involved three radiologists, showed a high degree of realistic clinical radiological appearance of the modelled breast components. Measured HU values of the printed structures are within the range of HU values used in the computational phantom. Moreover, measured physical parameters of the breast phantom, such as weight and linear dimensions, agreed very well with the corresponding ones of the computational breast model. Significance. The presented approach, based on a single FDM material, was found suitable for manufacturing of a physical breast phantom, which mimics well the 3D spatial distribution of the different breast tissues and their x-ray absorption properties. A

关键词： physical breast phantoms 3D printing fused-deposition modelling PLA filament MRI breast CT breast segmentation algorithm

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A novel image analysis algorithm reveals that media conditioned with chitosan and platelet-rich plasma biomaterial dose dependently increases fibroblast migration in a scratch assay

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BIOMEDICAL PHYSICS & ENGINEERING EXPRESS 2020年第6期6卷 065021-065021页

作者： Ahunon, Laura Milano, Fiona Chevrier, Anik Lavertu, Marc Polytech Montreal Biomed Engn Inst Montreal PQ Canada Ecole Natl Super Mines Mat Sci & Engn Dept Nancy France Polytech Montreal Chem Engn Dept Montreal PQ Canada

Chitosan (CS) and Platelet-Rich Plasma (PRP) both display interesting properties for wound healing applications. A hybrid CS-PRP biomaterial was previously developped, consisting of a freeze dried CS formulation solubilized in PRP that promotes tissue repair and regeneration. The purpose of the current study was to investigate the ability of the CS-PRP biomaterial to stimulate cell migration in vitro. Scratch assays revealed that CS-PRP significantly stimulates the migration rate of cells compared to cells in culture medium but not differently than PRP alone. The increase in the migration rate is dose-dependent at low dose and reaches a plateau corresponding with maximum cell motility. Cell migration rate as a function of the number of platelets that have degranulated in culture medium (to which total concentration of growth factors contributing to cell response is proportionnal), follows a modified Hill model. To analyze photographs taken during the assay and follow cell migration, an open source image analysis algorithm was developed: SAMScratch (Systematic Area Measurement of Scratch - available here: . Compared with other existing analysis tools, the algorithm is precise in the determination of the scratch area and performs equally well with usual and challenging images. This study resulted in the creation of a freely available application for scratch assay analysis and provided evidence that CS-PRP implants hold promise for treatment of wounds.

关键词： chitosan Platelet-rich plasma scratch assay growth factors segmentation algorithm in vitro cell migration Hill binding model

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Evaluation of the effect of myocardial localisation errors on myocardial blood flow estimates from DCE-MRI

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Journal of Cardiovascular Magnetic Resonance 2010年第1期12卷 1-2页

作者： John D Biglands Derek R Magee Roger Boyle Abdulghani Larghat Sven Plein Aleksandra Radjenovic Michael Jerosch-Herold The University of Leeds Leeds UK Brigham and Women's Hospital Boston MA USA

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Comparison of segmented thermal images versus a CT scanning for detection of maxillofacial pathology

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DENTOMAXILLOFACIAL RADIOLOGY 2019年第4期48卷 20180075-20180075页

作者： Macianskyte, Diana Monastyreckiene, Egle Basevicius, Algidas Adaskevicius, Rimas Lithuanian Univ Hlth Sci Clin Radiol Kaunas Lithuania Kaunas Univ Technol Dept Elect Power Syst Kaunas Lithuania

Objectives: To evaluate thermal images (TIs) by using an algorithm for optimized region of interest (ROI) and image segmentation, in order to find zones of the facial skin surface with asymmetrical temperature, and to test consistency with CT findings, to detect maxillofacial pathologies (i.e. tumours). Methods: The following steps for the TI evaluation were applied: data acquisition/pre-processing of frontal face and mouth projection, detection of face and mouth external contour, finding face and mouth symmetry axis, calculation of differences in average and maximal temperatures between left and right face and mouth sides, image segmentation of the selected ROI, and evaluation of diagnostic accuracy by comparing the TI results with CT findings. Results: In healthy subjects, the average temperature difference between left/right sides of facial and mouth ROI was negligible (0.02 +/- 0.21 degrees C and 0.05 +/- 0.19 degrees C, respectively;n = 23). In the presence of tumour, the average temperature difference was higher in corresponding TIs (0.47 +/- 0.1 degrees C and 0.66 +/- 0.1 degrees C, for facial and mouth ROI, respectively;n = 19, p < 0.05). For large tumours, thermal asymmetry in the corresponding TI is easily detected, and image segmentation is optional for finding the affected zone. For small or deeply localized tumours, segmentation of the mouth cavity of the ROI was required for the detection of hot and cold spots. Conclusions: Asymmetrical temperature zones and their location as detected from thermal images coincide well with the presence and localization of maxillofacial pathologies (i.e. tumours) established by CT. However, accurate information could often be obtained only after application of image segmentation algorithm to the selected ROI.

关键词： Infrared thermal imaging CT segmentation algorithm maxillofacial pathology

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Optimizing rat and human blood cells sampling for in silico morphometric analysis

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ACTA HISTOCHEMICA 2022年第6期124卷 151917页

作者： Zamora-Bello, Isaac Hernandez-Baltazar, Daniel Rodriguez-Landa, Juan Francisco Rivadeneyra-Dominguez, Eduardo Univ Veracruzana Fac Quim Farmaceut Biol Xalapa Veracruz Mexico Consejo Nacl Ciencia & Tecnol CONACyT Mexico City Mexico Univ Veracruzana Inst Neuroetol Xalapa Veracruz Mexico Univ Veracruzana Fac Quim Farmaceut Biol Circuito Gonzalo Aguirre Beltran S-NZona Univ Xalapa 91000 Veracruz Mexico

Measurements of Morphometric Parameters of the Blood Cells (MPBC) are key for the diagnosis of both mental and metabolic diseases. Several manual approaches or computational methodologies are useful to provide reliable clinical diagnosis. The sample processing and data analysis is relevant, however the sample handling on the pre-analytical phase remains scarcely evaluated. The main goal of this study was to favor the preservation of blood smear using a histological resin. This strategy lead us two practical approaches, give a detailed morphometric description of white blood cells and establish reference intervals in male Wistar rats, which are scarcely reported. Blood smears from male Wistar rats (n = 120) and adult men were collected at room temperature. The integrity of Wright-stained cells was evaluated by an in silico image analysis from rat and human blood smear preserved with a toluene-based synthetic resin mounting medium. A single sample of human blood was used as a control of procedure. The reference intervals was established by cell counting. Based on the results of segmentation algorithm followed by an automatic thresholding analysis, the incorporation of resin favor the conservation of cell blood populations, and lead to identify morphologic features such as nucleus/cytoplasmic shape, granules presence and DNA appearance in nucleus of white blood cells. The use of a histological resin could favor a fast and efficient sample handling in silico MPBC measurements both in the species studied as in wild animals.

关键词： Automatic thresholding Blood smear examination Hematic cytometry Human segmentation algorithm Wistar rat

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A microhardness indentation point cloud segmentation method based on voxel cloud connectivity segmentation

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Measurement: Sensors 2021年 18卷

作者： Shi Wei Shi Chengyao Chen Shilin Zhang Kailin Changcheng Institute of Metrology & Measurement Beijing China Beihang University Beijing China

In order to accurately extract the effective area of microhardness indentation obtained by laser scanning confocal microscope, the indentation point cloud segmentation method is studied based on over-segmentation using voxel cloud connectivity segmentation. Further, a microhardness indentation point cloud segmentation algorithm is proposed. The proposed method can determine the belonging area of the point cloud by combining multiple feature score models, and can achieve the segmentation and extraction of ultra-microhardness indentation data where the characteristics of indentation area are not obvious, or the data point is dense. The experimental results show that the method can extract the indentation area accurately, and the repeatability and consistency of extraction is good.

关键词： Voxel cloud connectivity segmentation (VCCS) Ultra-microhardness Indentation point cloud segmentation algorithm Score model

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