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A process that involves the registration of two brain Magnetic Resonance Imaging (MRI) acquisitions is proposed for the subtraction between previous and current images at two different follow-up (FU) time points. Brain tumours can be non-cancerous (benign) or cancerous (malignant). Treatment choices for these conditions rely on the type of brain tumour as well as its size and location. Brain cancer is a fast-spreading tumour that must be treated in time. MRI is commonly used in the detection of early signs of abnormality in the brain area because it provides clear details. Abnormalities include the presence of cysts, haematomas or tumour cells. A sequence of images can be used to detect the progression of such abnormalities. A previous study on conventional (CONV) visual reading reported low accuracy and speed in the early detection of abnormalities, specifically in brain images. It can affect the proper diagnosis and treatment of the patient. A digital subtraction technique that involves two images acquired at two interval time points and their subtraction for the detection of the progression of abnormalities in the brain image was proposed in this study. MRI datasets of five patients, including a series of brain images, were retrieved retrospectively in this study. All methods were carried out using the MATLAB programming platform. ROI volume and diameter for both regions were recorded to analyse progression details, location, shape variations and size alteration of tumours. This study promotes the use of digital subtraction techniques on brain MRIs to track any abnormality and achieve early diagnosis and accuracy whilst reducing reading time. Thus, improving the diagnostic information for physicians can enhance the treatment plan for patients.

2D digital subtraction angiography (DSA) is utilized qualitatively to assess blood velocity changes that occur during arterial interventions. Quantitative angiographic metrics, such as blood velocity, could be used to standardize endpoints during angiographic interventions.

To evaluate a modified subtraction coronary computed tomography angiography (CCTA) technique with a two-breathhold approach in terms of image quality and stenosis grading of calcified coronary segments and in the detection of significant coronary stenosis in segments with severe calcification.

Depth information has been used in computer vision for a wide variety of tasks. Since active range sensors are currently available at low cost, high-quality depth maps can be used as relevant input for many applications. Background subtraction and video segmentation algorithms can be improved by fusing depth and color inputs, which are complementary and allow one to solve many classic color segmentation issues. In this paper, we describe one fusion method to combine color and depth based on an advanced color-based algorithm. This technique has been evaluated by means of a complete dataset recorded with Microsoft Kinect, which enables comparison with the original method. The proposed method outperforms the others in almost every test, showing more robustness to illumination changes, shadows, reflections and camouflage.

A number of restricted diffusion (RD) imaging techniques, such as diffusion kurtosis (DK) imaging and Q space imaging, have been developed and proven to be useful for the diagnosis of diseases, including cerebral gliomas and cerebrovascular infarction. In particular, apparent diffusion coefficient (ADC) subtraction method (ASM) imaging has become available recently as a novel RD imaging technique. ASM is based on the difference between the ADC values in an image pair of two ADC maps, ADC basic (ADCb) and ADC modify (ADCm), which are created from diffusion-weighted images taken using short and long effective diffusion times, respectively. The present study aimed to assess the potential of different types of ASM imaging by comparing them with DK imaging which is the gold-standard RD imaging technique. In the present basic study using both polyethylene glycol phantom and cell-containing bio-phantom, three different types of ASM images were created using different calculation processes. ASM/A is an image calculated by dividing the absolute difference between ADCb and ADCm by ADCb several times. By contrast, ASM/S is an image created by dividing the absolute difference between ADCb and ADCm by the standard deviation of ADCb several times. As for positive ASM/A image (PASM/A), the positive image, which was resultant after subtracting ADCb from ADCm, was divided by ADCb several times. A comparison was made between the types of ASM and DK images. The results showed the same tendency between ASM/A in addition to both ASM/S and PASM/A. By increasing the number of divisions by ADCb from three to five times, ASM/A images transformed from DK-mimicking to more RD-sensitive images compared with DK images. These observations suggest that ASM/A images may prove useful for future clinical applications in RD imaging protocols for the diagnosis of diseases.

Pedicle subtraction osteotomy (PSO) is an invasive surgical technique allowing the restoration of a well-balanced sagittal profile, however, the risks of pseudarthrosis and instrumentation breakage are still high. Literature studied primary stability and posterior instrumentation loads, neglecting the load shared by the anterior column, which is fundamental to promote fusion early after surgery. The study aimed at quantifying the load-sharing occurring after PSO procedure across the ventral spinal structures and the posterior instrumentation, as affected by simple bilateral fixation alone, with interbody cages adjacent to PSO level and supplementary accessory rods. Lumbar spine segments were loaded in vitro under flexion-extension, lateral bending, and torsion using an established spine tester. Digital image correlation (DIC) and strain-gauge (SG) analyses measured, respectively, the full-field strain distribution on the ventral surface of the spine and the local strain on posterior primary rods. Ventral strains considerably decreased following PSO and instrumentation, confirming the effectiveness of posterior load-sharing. Supplemental accessory rods considerably reduced the posterior rod strains only with interbody cages, but the ventral strains were unaffected: this indicates that the load transfer across the osteotomy could be promoted, thus explaining the higher fusion rate with decreased rod fracture risk reported in clinical literature.

Digital subtraction angiography (DSA) is an imaging technique used to diagnose and confirm abnormal lesions of cerebral blood vessels in various situations. Several complications such as cerebral infarction, contrast-induced allergy, and angio-site hematoma or infection can occur after DSA. We investigated complication rates and risk factors related to DSA.

We developed a conceptually new subtraction strategy for the detection and isolation of target DNA and/or RNA from complex nucleic acid mixtures, called Primer Extension Enrichment Reaction (PEER). PEER uses adapters and class IIS restriction enzymes to generate tagged oligonucleotides from dsDNA fragments derived from specimens containing an unknown target ('tester'). Subtraction is achieved by selectively disabling these oligonucleotides by extension reaction using ddNTPs and a double stranded DNA template generated from a pool of normal specimens ('driver'). Primers that do not acquire ddNTP are used to capture and amplify the unique target DNA from the original tester dsDNA. We successfully applied PEER to specimens containing known infectious agents (Hepatitis B Virus and Walrus Calicivirus) and demonstrated that it has higher efficiency than the best comparable technique. The strategy used for PEER is versatile and can be adapted for the identification of known and unknown pathogens and mutations, differential expression studies and other applications that allow the use of subtractive strategies.

Congenital heart disease (CHD) is a significant cause of mortality in infants and adults. Currently human genomic analysis has identified a number of candidate genes in these patients. These genes span diverse categories of gene function suggesting that despite the similarity in cardiac lesion, the underlying pathophysiology may be different. In fact, patients with similar CHDs can have drastically different outcomes, including a dramatic decrease in myocardial function. To test these human candidate genes for their impact on myocardial function, we need efficient animals models of disease. For this purpose, we paired Xenopus tropicalis with our microangiography technique, hemoglobin contrast subtraction angiography (HCSA). To demonstrate the gene-teratogen-physiology relationship, we modeled human cardiomyopathy in tadpoles. First we depleted the sarcomeric protein myosin heavy chain 6 (myh6) expression using morpholino oligos. Next, we exposed developing embryos to the teratogen ethanol and in both conditions showed varying degrees of cardiac dysfunction. Our results demonstrate that HCSA can distinguish biomechanical phenotypes in the context of gene dysfunction or teratogen. This approach can be used to screen numerous candidate CHD genes or suspected teratogens for their effect on cardiac function.

The present study introduces a subtraction-average-based optimization algorithm (SAOA), a unique enhanced evolutionary technique for solving engineering optimization problems. The typical SAOA works by subtracting the average of searcher agents from the position of population members in the search space. To increase searching capabilities, this study proposes an improved SAO (ISAO) that incorporates a cooperative learning technique based on the leader solution. First, after considering testing on different standard mathematical benchmark functions, the proposed ISAOA is assessed in comparison to the standard SAOA. The simulation results declare that the proposed ISAOA establishes great superiority over the standard SAOA. Additionally, the proposed ISAOA is adopted to handle power system applications for Thyristor Controlled Series Capacitor (TCSC) allocation-based losses reduction in electrical power grids. The SAOA and the proposed ISAOA are employed to optimally size the TCSCs and simultaneously select their installed transmission lines. Both are compared to two recent algorithms, the Artificial Ecosystem Optimizer (AEO) and AQuila Algorithm (AQA), and two other effective and well-known algorithms, the Grey Wolf Optimizer (GWO) and Particle Swarm Optimizer (PSO). In three separate case studies, the standard IEEE-30 bus system is used for this purpose while considering varying numbers of TCSC devices that will be deployed. The suggested ISAOA's simulated implementations claim significant power loss reductions for the three analyzed situations compared to the GWO, AEO, PSO, and AQA.

Background: Pedicle subtraction osteotomy (PSO) is a powerful tool for sagittal plane correction in patients with rigid adult spinal deformity (ASD); however, it is associated with high intraoperative blood loss and the increased risk of durotomy. The objective of the present study was to identify intraoperative techniques and baseline patient factors capable of predicting intraoperative durotomy. Methods: A tri-institutional database was retrospectively queried for all patients who underwent PSO for ASD. Data on baseline comorbidities, surgical history, surgeon characteristics and intraoperative maneuvers were gathered. PSO aggressiveness was defined as conventional (Schwab 3 PSO) or an extended PSO (Schwab type 4). The primary outcome of the study was the occurrence of durotomy intraoperatively. Univariable analyses were performed with Mann-Whitney U tests, Chi-squared analyses, and Fisher's exact tests. Statistical significance was defined by p < 0.05. Results: One hundred and sixteen patients were identified (mean age 61.9 ± 12.6 yr; 44.8% male), of whom 51 (44.0%) experienced intraoperative durotomy. There were no significant differences in baseline comorbidities between those who did and did not experience durotomy, with the exception that baseline weight and body mass index were higher in patients who did not suffer durotomy. Prior surgery (OR 2.73; 95% CI [1.13, 6.58]; p = 0.03) and, more specifically, prior decompression at the PSO level (OR 4.23; 95% CI [1.92, 9.34]; p < 0.001) was predictive of durotomy. A comparison of surgeon training showed no statistically significant difference in durotomy rate between fellowship and non-fellowship trained surgeons, or between orthopedic surgeons and neurosurgeons. The PSO level, PSO aggressiveness, the presence of stenosis at the PSO level, nor the surgical instrument used predicted the odds of durotomy occurrence. Those experiencing durotomy had similar hospitalization durations, rates of reoperation and rates of nonroutine discharge. Conclusions: In this large multisite series, a history of prior decompression at the PSO level was associated with a four-fold increase in intraoperative durotomy risk. Notably the use of extended (versus) standard PSO, surgical technique, nor baseline patient characteristics predicted durotomy. Durotomies occurred in 44% of patients and may prolong operative times. Additional prospective investigations are merited.

A three-dimensional (3D) cardiovascular magnetic resonance (CMR) vessel wall imaging (VWI) technique based on 3D T1 weighted (T1w) Sampling Perfection with Application-optimized Contrast using different flip angle Evolutions (SPACE) has recently been used as a promising CMR imaging modality for evaluating extra-cranial and intra-cranial vessel walls. However, this technique is yet to be validated against the current diagnostic imaging standard. We therefore aimed to evaluate the diagnostic performance of 3D CMR VWI in characterizing carotid disease using intra-arterial digital subtraction angiography (DSA) as a reference.

When imaging brain vasculature with optical coherence tomography angiography (OCTA), volumetric analysis of cortical vascular networks in OCTA datasets is frequently challenging due to the presence of artifacts, which appear as multiple-scattering tails beneath superficial large vessels in OCTA images. These tails shadow underlying small vessels, making the assessment of vascular morphology in the deep cortex difficult. In this work, we introduce an image processing technique based on mean subtraction of the depth profile that can effectively reduce these tails to better reveal small hidden vessels compared to the current tail removal approach. With the improved vascular image quality, we demonstrate that this simple method can provide better visualization of three-dimensional vascular network topology for quantitative cerebrovascular studies.

BACKGROUND This study was conducted to investigate the reliability and efficacy of polyvinyl alcohol combined with coils in the embolization of iatrogenic renal vascular injury with the assistance of 3-dimensional digital subtraction angiography (3D-DSA). MATERIAL AND METHODS Twenty-six patients with minimally invasive renal bleeding who underwent transarterial embolization from January 2012 to January 2019 in our hospital were included in the study. We obtained demographic data from these patients, as well as information on clinical presentation, renal procedures used for treatment, and perioperative details. The changes in renal function tests, serum hemoglobin, serum hematocrit, and technetium Tc 99m dimercaptosuccinic acid (99mTc-DMSA) levels pre- and postembolization were compared. In addition, the embolic area and the technical and clinical success rates were analyzed. Finally, an angiographic manifestation of the renal artery, 3D-DSA, and the effect of embolization were analyzed retrospectively. RESULTS All patients achieved technical and clinical success after embolization (100%, 26/26). There were no significant differences between pre- and postoperative estimated glomerular filtration rate, serum parameters, and 99mTc-DMSA. The embolic area was 12%±10%. Patients did not exhibit severe complications during the follow-up period. CONCLUSIONS Proximal embolization technique assisted by 3D-DSA for renal iatrogenic hemorrhage and vascular lesions is both safe and efficacious, offering high rates for both clinical and technical success. It maximizes the protection of the kidney and reduces the rate of renal resection.

To compare the effects of bone suppression imaging using deep learning (BSp-DL) based on a generative adversarial network (GAN) and bone subtraction imaging using a dual energy technique (BSt-DE) on radiologists' performance for pulmonary nodule detection on chest radiographs (CXRs).

Subtraction technique has been broadly applied for target gene discovery. However, most current protocols apply relative differential subtraction and result in great amount clone mixtures of unique and differentially expressed genes. This makes it more difficult to identify unique or target-orientated expressed genes. In this study, we developed a novel method for subtraction at mRNA level by integrating magnetic particle technology into driver preparation and tester-driver hybridization to facilitate uniquely expressed gene discovery between peanut immature pod and leaf through a single round subtraction. The resulting target clones were further validated through polymerase chain reaction screening using peanut immature pod and leaf cDNA libraries as templates. This study has resulted in identifying several genes expressed uniquely in immature peanut pod. These target genes can be used for future peanut functional genome and genetic engineering research.

In EEG data acquired in the presence of fMRI, gradient-related spike artifacts contaminate the signal following the common preprocessing step of average artifact subtraction. Spike artifacts compromise EEG data quality since they overlap with the EEG signal in frequency, thereby confounding frequency-based inferences on activity. As well, spike artifacts can inflate or deflate correlations among time series, thereby confounding inferences on functional connectivity. We present Schrödinger filtering, which uses the Schrödinger equation to decompose the spike-containing input. The basis functions of the decomposition are localized and pulse-shaped, and selectively capture the various input peaks, with the spike components clustered at the beginning of the spectrum. Schrödinger filtering automatically subtracts the spike components from the data. On real and simulated data, we show that Schrödinger filtering (1) simultaneously accomplishes high spike removal and high signal preservation without affecting evoked activity, and (2) reduces spurious pairwise correlations in spontaneous activity. In these regards, Schrödinger filtering was significantly better than three other despiking techniques: median filtering, amplitude thresholding, and wavelet denoising. These results encourage the use of Schrödinger filtering in future EEG-fMRI pipelines, as well as in other spike-related applications (e.g., fMRI motion artifact removal or action potential extraction).

A novel machine learning framework that is able to consistently detect, localize, and measure the severity of human congenital cleft lip anomalies is introduced. The ultimate goal is to fill an important clinical void: to provide an objective and clinically feasible method of gauging baseline facial deformity and the change obtained through reconstructive surgical intervention. The proposed method first employs the StyleGAN2 generative adversarial network with model adaptation to produce a normalized transformation of 125 faces, and then uses a pixel-wise subtraction approach to assess the difference between all baseline images and their normalized counterparts (a proxy for severity of deformity). The pipeline of the proposed framework consists of the following steps: image preprocessing, face normalization, color transformation, heat-map generation, morphological erosion, and abnormality scoring. Heatmaps that finely discern anatomic anomalies visually corroborate the generated scores. The proposed framework is validated through computer simulations as well as by comparison of machine-generated versus human ratings of facial images. The anomaly scores yielded by the proposed computer model correlate closely with human ratings, with a calculated Pearson's r score of 0.89. The proposed pixel-wise measurement technique is shown to more closely mirror human ratings of cleft faces than two other existing, state-of-the-art image quality metrics (Learned Perceptual Image Patch Similarity and Structural Similarity Index). The proposed model may represent a new standard for objective, automated, and real-time clinical measurement of faces affected by congenital cleft deformity.

A method for simultaneous electrochemical detection of brain tissue PO2 (PtO2) and pH changes together with neuronal activity using a modified form of fast cyclic voltammetry with carbon fiber electrodes is described. This technique has been developed for in vivo applications and recordings from discrete brain nuclei in experimental animals. The small size of the carbon fiber electrode (⌀7 μm, length <100 μm) ensures minimal disruption of the brain tissue and allows recordings from small brain areas. Sample rate (up to 4 Hz) is sufficient to resolve rapid changes in PtO2 and pH that follow changes in neuronal activity and metabolism. Rapid switching between current and voltage recordings allows combined electrochemical detection and monitoring of extracellular action potentials. For simultaneous electrochemical detection of PtO2 and pH, two consecutive trapezoidal voltage ramps are applied with double differential-subtraction of the background current. This enables changes in current caused by protons and oxygen to be detected separately with minimal interference between the two. The profile of PtO2 changes evoked by increases in local neuronal activity recorded using the described technique was very similar to that of blood-oxygen-level-dependent responses recorded using fMRI. This voltammetric technique can be combined with fMRI and brain vessel imaging to study the metabolic mechanisms underlying neurovascular coupling response with much greater spatial and temporal resolution than is currently possible.