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BMC Medical Research Methodology Sep 2021The data obtained from the counting process is known as the count data. In practice, the counting can be done at the same time or the time of the count is not the same....
BACKGROUND
The data obtained from the counting process is known as the count data. In practice, the counting can be done at the same time or the time of the count is not the same. To test either the K counts are differed significantly or not, the Chi-square test for K counts is applied.
RESULTS
The paper presents the Chi-square tests for K counts under neutrosophic statistics. The test statistic of the proposed test when K counts are recorded at the same time and different time are proposed. The testing procedure of the proposed test is explained with the help of pulse count data.
CONCLUSIONS
From the analysis of pulse count data, it can be concluded that the proposed test suggests the cardiologists use different treatment methods on patients. In addition, the proposed test gives more information than the traditional test under uncertainty.
Topics: Chi-Square Distribution; Humans; Uncertainty
PubMed: 34592943
DOI: 10.1186/s12874-021-01400-z -
Physics in Medicine and Biology Jul 2023In photon counting detectors (PCDs), electric pulses induced by two or more x-ray photons can pile up and result in count losses when their temporal separation is less...
In photon counting detectors (PCDs), electric pulses induced by two or more x-ray photons can pile up and result in count losses when their temporal separation is less than the detector dead time. The correction of pulse pile-up-induced count loss is particularly difficult for paralyzable PCDs since a given value of recorded counts can correspond to two different values of true photon interactions. In contrast, charge (energy) integrating detectors work by integrating collected electric charge induced by x-rays over time and do not suffer from pile-up losses. This work introduces an inexpensive readout circuit element to the circuits of PCDs to simultaneously collect time-integrated charge to correct pile-up-induced count losses.Prototype electronics were constructed to collect time-integrated charges simultaneously with photon counts. A splitter was used to feed the electric signal in parallel to both a digital counter and a charge integrator. After recording PCD counts and integrating collected charge, a lookup table can be generated to map raw counts in the total- and high-energy bins and total charge to estimate pile-up-free true counts. Proof-of-concept imaging experiments were performed with a CdTe-based PCD array to test this method.The proposed electronics successfully recorded photon counts and time-integrated charge simultaneously, and whereas photon counts exhibited paralyzable pulse pile-up, time-integrated charge using the same electric signal as the counts measurement was linear with x-ray flux. With the proposed correction, paralyzable PCD counts became linear with input flux for both total- and high-energy bins. At high flux levels, uncorrected post-log measurements of PMMA objects severely overestimated radiological path lengths for both energy bins. After the proposed correction, the non-monotonic measurements again became linear with flux and accurately represented the true radiological path lengths. No impact on the spatial resolution was observed after the proposed correction in images of a line-pair test pattern.Time-integrated charge can be used to correct for pulse pile-up in paralyzable PCDs where analytical solutions may be difficult to use, and integrated charge can be collected simultaneously with counts using inexpensive electronics.
Topics: Cadmium Compounds; Photons; Tellurium; Quantum Dots
PubMed: 37379858
DOI: 10.1088/1361-6560/ace2a9 -
Journal of Environmental Management Feb 2023Long-term monitoring of wildlife numbers traditionally uses observers, which are frequently inefficient and inaccurate due to their variable experience/training, are...
Long-term monitoring of wildlife numbers traditionally uses observers, which are frequently inefficient and inaccurate due to their variable experience/training, are costly and difficult to sustain over time. Furthermore, there are other inhibiting factors for wildlife counting, such as: inhabiting inaccessible areas, fear of humans, and nocturnal behavior. There is a need to develop new technologies that will automatically identify and count wild animals in order to determine the appropriate management protocol. In this study, an advanced and accurate method for automatically calculating the number of cranes (Grus grus), using thermal cameras at night and visible light (RGB) cameras during the day onboard unmanned aerial vehicles (UAVs), based on image analysis and computer vision, was developed. The cranes congregate at night in a large communal roost, making it possible to count the birds while they are relatively static and all together. Each bird was counted individually by creating a standardized tool to determine population numbers for management, using image analysis and automatic processing. A dedicated algorithm was developed that aimed to identify the cranes based on their spectral characteristics (typical temperature, shape, size) and to effectively separate the cranes from the typical background. The automatic segmentation and counting of roosting common cranes using UAV nighttime thermal images had an Overall Accuracy (OA) of 91.47%, User's Accuracy (UA) of 99.68%, and Producer's Accuracy (PA) of 91.74%. The computer vision and machine learning algorithm based on the YOLO v3 platform of daytime RGB UAV images of common cranes at the feeding station yielded an overall loss accuracy level of 2.25%, with a mean square error of 1.87, OA of 94.51%, UA of 99.91%, PA of 94.59%. These results are highly encouraging, and although the algorithms were developed for the purpose of counting cranes, they could be adapted for other counting purposes for wildlife management.
Topics: Animals; Humans; Unmanned Aerial Devices; Animals, Wild; Algorithms; Computers; Image Processing, Computer-Assisted
PubMed: 36516707
DOI: 10.1016/j.jenvman.2022.116948 -
Bioinformatics (Oxford, England) Sep 2018Counting molecules using next-generation sequencing (NGS) suffers from PCR amplification bias, which reduces the accuracy of many quantitative NGS-based experimental...
MOTIVATION
Counting molecules using next-generation sequencing (NGS) suffers from PCR amplification bias, which reduces the accuracy of many quantitative NGS-based experimental methods such as RNA-Seq. This is true even if molecules are made distinguishable using unique molecular identifiers (UMIs) before PCR amplification, and distinct UMIs are counted instead of reads: Molecules that are lost entirely during the sequencing process will still cause underestimation of the molecule count, and amplification artifacts like PCR chimeras create phantom UMIs and thus cause over-estimation.
RESULTS
We introduce the TRUmiCount algorithm to correct for both types of errors. The TRUmiCount algorithm is based on a mechanistic model of PCR amplification and sequencing, whose two parameters have an immediate physical interpretation as PCR efficiency and sequencing depth and can be estimated from experimental data without requiring calibration experiments or spike-ins. We show that our model captures the main stochastic properties of amplification and sequencing, and that it allows us to filter out phantom UMIs and to estimate the number of molecules lost during the sequencing process. Finally, we demonstrate that the phantom-filtered and loss-corrected molecule counts computed by TRUmiCount measure the true number of molecules with considerably higher accuracy than the raw number of distinct UMIs, even if most UMIs are sequenced only once as is typical for single-cell RNA-Seq.
AVAILABILITY AND IMPLEMENTATION
TRUmiCount is available at http://www.cibiv.at/software/trumicount and through Bioconda (http://bioconda.github.io).
SUPPLEMENTARY INFORMATION
Supplementary information is available at Bioinformatics online.
Topics: Algorithms; High-Throughput Nucleotide Sequencing; Polymerase Chain Reaction; RNA; Sequence Analysis, RNA; Software
PubMed: 29672674
DOI: 10.1093/bioinformatics/bty283 -
Healthcare Technology Letters Aug 2019A complete blood cell count is an important test in medical diagnosis to evaluate overall health condition. Traditionally blood cells are counted manually using...
A complete blood cell count is an important test in medical diagnosis to evaluate overall health condition. Traditionally blood cells are counted manually using haemocytometer along with other laboratory equipment's and chemical compounds, which is a time-consuming and tedious task. In this work, the authors present a machine learning approach for automatic identification and counting of three types of blood cells using 'you only look once' (YOLO) object detection and classification algorithm. YOLO framework has been trained with a modified configuration BCCD Dataset of blood smear images to automatically identify and count red blood cells, white blood cells, and platelets. Moreover, this study with other convolutional neural network architectures considering architecture complexity, reported accuracy, and running time with this framework and compare the accuracy of the models for blood cells detection. They also tested the trained model on smear images from a different dataset and found that the learned models are generalised. Overall the computer-aided system of detection and counting enables us to count blood cells from smear images in less than a second, which is useful for practical applications.
PubMed: 31531224
DOI: 10.1049/htl.2018.5098 -
BMC Bioinformatics Mar 2022Locomotive behaviors are a rapid evaluation indicator reflecting whether the nervous system of worms is damaged, and has been proved to be sensitive to chemical...
BACKGROUND
Locomotive behaviors are a rapid evaluation indicator reflecting whether the nervous system of worms is damaged, and has been proved to be sensitive to chemical toxicity. In many toxicological studies, C. elegans head thrashes is a key indicator of locomotive behaviors to measure the vitality of worms. In previous studies, the number of head thrashes was manually counted, which is time-consuming and labor-intensive.
RESULTS
This paper presents an automatic recognition and counting method for head thrashes behavior of worms from experimental videos. First, the image processing algorithm is designed for worm morphology features calculation, mean gray values of head and tail are used to locate the head of worm accurately. Next, the worm skeleton is extracted and divided into equal parts. The angle formulas are used to calculate the bending angle of the head of worm. Finally, the number of head thrashes is counted according to the bending angle of the head in each frame. The robustness of the proposed algorithm is evaluated by comparing the counting results of the manual counting. It is proved that the proposed algorithm can recognize the occurrence of head thrashes of C. elegans of different strains. In addition, the difference of the head thrashes behavior of different worm strains is analyzed, it is proved that the relationship between worm head thrashes behavior and lifespan.
CONCLUSIONS
A new method is proposed to automatically count the number of head thrashes of worms. This algorithm makes it possible to count the number of head thrashes from the worm videos collected by the automatic tracking system. The proposed algorithm will play an important role in toxicological research and worm vitality research. The code is freely available at https://github.com/hthana/HTC .
Topics: Algorithms; Animals; Caenorhabditis elegans; Image Processing, Computer-Assisted; Longevity
PubMed: 35255825
DOI: 10.1186/s12859-022-04622-0 -
The Journal of Neuroscience Nursing :... Aug 2020When tested in a controlled clinic environment, individuals with neuromuscular-related symptoms may complete motor tasks within normal predicted ranges. However,...
BACKGROUND
When tested in a controlled clinic environment, individuals with neuromuscular-related symptoms may complete motor tasks within normal predicted ranges. However, measuring activity at home may better reflect typical motor performance. The accuracy of accelerometry measurements in individuals with congenital muscular dystrophy (CMD) is unknown. We aimed to compare accelerometry and manual step counts and assess free-living physical activity intensity in individuals with CMD using accelerometry.
METHODS
Ambulatory pediatric CMD participants (n = 9) performed the 6-minute walk test in clinic while wearing ActiGraph GT3X accelerometer devices. During the test, manual step counting was conducted to assess concurrent validity of the ActiGraph step count in this population using Bland-Altman analysis. In addition, activity intensity of 6 pediatric CMD participants was monitored at home with accelerometer devices for an average of 7 days. Cut-point values previously validated for neuromuscular disorders were used for data analysis.
RESULTS
Bland-Altman and intraclass correlation analyses showed no concurrent validity between manual and ActiGraph-recorded step counts. Fewer steps were recorded by ActiGraph step counts compared with manual step counts (411 ± 74 vs 699 ± 43, respectively; P = .004). Although improved, results were in the same direction with the application of low-frequency extension filters (587 ± 40 vs 699 ± 43, P = .03). ActiGraph step-count data did not correlate with manual step count (Spearman ρ = 0.32, P = .41; with low-frequency extension: Spearman ρ = 0.45, P = .22). Seven-day physical activity monitoring showed that participants spent more than 80% of their time in the sedentary activity level.
CONCLUSIONS
In a controlled clinic setting, step count was significantly lower by ActiGraph GT3X than by manual step counting, possibly because of the abnormal gait in this population. Additional studies using triaxial assessment are needed to validate accelerometry measurement of activity intensity in individuals with CMD. Accelerometry outcomes may provide valuable measures and complement the 6-minute walk test in the assessment of treatment efficacy in CMD.
Topics: Accelerometry; Adolescent; Child; Female; Humans; Male; Motor Activity; Muscular Dystrophies; Reproducibility of Results
PubMed: 32511172
DOI: 10.1097/JNN.0000000000000519 -
Scientific Reports Jan 2024Quantifying bacterial cell numbers is crucial for experimental assessment and reproducibility, but the current technologies have limitations. The commonly used colony...
Quantifying bacterial cell numbers is crucial for experimental assessment and reproducibility, but the current technologies have limitations. The commonly used colony forming units (CFU) method causes a time delay in determining the actual numbers. Manual microscope counts are often error-prone for submicron bacteria. Automated systems are costly, require specialized knowledge, and are erroneous when counting smaller bacteria. In this study, we took a different approach by constructing three sequential generations (G1, G2, and G3) of counter-on-chip that accurately and timely count small particles and/or bacterial cells. We employed 2-photon polymerization (2PP) fabrication technology; and optimized the printing and molding process to produce high-quality, reproducible, accurate, and efficient counters. Our straightforward and refined methodology has shown itself to be highly effective in fabricating structures, allowing for the rapid construction of polydimethylsiloxane (PDMS)-based microfluidic devices. The G1 comprises three counting chambers with a depth of 20 µm, which showed accurate counting of 1 µm and 5 µm microbeads. G2 and G3 have eight counting chambers with depths of 20 µm and 5 µm, respectively, and can quickly and precisely count Escherichia coli cells. These systems are reusable, accurate, and easy to use (compared to CFU/ml). The G3 device can give (1) accurate bacterial counts, (2) serve as a growth chamber for bacteria, and (3) allow for live/dead bacterial cell estimates using staining kits or growth assay activities (live imaging, cell tracking, and counting). We made these devices out of necessity; we know no device on the market that encompasses all these features.
Topics: Reproducibility of Results; Biological Assay; Cell Count; Cell Tracking; Escherichia coli
PubMed: 38191788
DOI: 10.1038/s41598-023-51014-2 -
Archives of Pathology & Laboratory... Nov 2020Mitotic count is an important histologic criterion for grading and prognostication in phyllodes tumors (PTs). Counting mitoses is a routine practice for pathologists...
CONTEXT.—
Mitotic count is an important histologic criterion for grading and prognostication in phyllodes tumors (PTs). Counting mitoses is a routine practice for pathologists evaluating neoplasms, but different microscopes, variable field selection, and areas have led to possible misclassification.
OBJECTIVE.—
To determine whether 10 high-power fields (HPFs) or whole slide mitotic counts correlated better with PT clinicopathologic parameters using digital pathology (DP). We also aimed to find out whether this study might serve as a basis for an artificial intelligence (AI) protocol to count mitosis.
DESIGN.—
Representative slides were chosen from 93 cases of PTs diagnosed between 2014 and 2015. The slides were scanned and viewed with DP. Mitotic counting was conducted on the whole slide image, before choosing 10 HPFs and demarcating the tumor area in DP. Values of mitoses per millimeter squared were used to compare results between 10 HPFs and the whole slide. Correlations with clinicopathologic parameters were conducted.
RESULTS.—
Both whole slide counting of mitoses and 10 HPFs had similar statistically significant correlation coefficients with grade, stromal atypia, and stromal hypercellularity. Neither whole slide mitotic counts nor mitoses per 10 HPFs showed statistically significant correlations with patient age and tumor size.
CONCLUSIONS.—
Accurate mitosis counting in breast PTs is important for grading. Exploring machine learning on digital whole slides may influence approaches to training, testing, and validation of a future AI algorithm.
Topics: Adult; Artificial Intelligence; Breast Neoplasms; Cytodiagnosis; Female; Humans; Microscopy; Middle Aged; Mitosis; Mitotic Index; Pathology, Clinical; Phyllodes Tumor; Reproducibility of Results; Sensitivity and Specificity
PubMed: 32150458
DOI: 10.5858/arpa.2019-0435-OA -
Asian Journal of Transfusion Science 2023Among the blood counts, platelet count is most often reported with inconsistency. Many of the analyzers work on electrical impedance principle for red blood cell (RBC)...
Among the blood counts, platelet count is most often reported with inconsistency. Many of the analyzers work on electrical impedance principle for red blood cell (RBC) and platelet counting. However, with this technology, factors such as fragmented RBCs, microcytes, cytoplasmic fragments of leukemic cells, lipid particles, fungal yeast forms, and bacteria are known to interfere with platelet count and give spuriously elevated platelet counts. A 72-year-old male was admitted for the treatment of dengue infection who had serial platelet count monitoring. He had an initial platelet count of 48,000/cumm which suddenly improved to 2.6 lakhs within 6 h without any platelet transfusion. Peripheral smear however did not correlate with the machine-derived count. Repeat test after 6 h yielded a result of 56,000/cumm which correlated well with the peripheral smear. This falsely elevated count was due to the presence of lipid particles as the sample was drawn in the postprandial state.
PubMed: 37188023
DOI: 10.4103/ajts.ajts_65_21