Tree crown segmentation based on a tree crown density model derived from Airborne Laser Scanning

ABSTRACT

This letter describes a new algorithm for automatic tree crown delineation based on a model of tree crown density, and its validation. The tree crown density model was first used to create a correlation surface, which was then input to a standard watershed segmentation algorithm for delineation of tree crowns. The use of a model in an early step of the algorithm neatly solves the problem of scale selection. In earlier studies, correlation surfaces have been used for tree crown segmentation, involving modelling tree crowns as solid geometric shapes. The new algorithm applies a density model of tree crowns, which improves the model’s suitability for segmentation of Airborne Laser Scanning (ALS) data because laser returns are located inside tree crowns. The algorithm was validated using data acquired for 36 circular (40 m radius) field plots in southern Sweden. The algorithm detected high proportions of field-measured trees (40–97% of live trees in the 36 field plots: 85% on average). The average proportion of detected basal area (cross-sectional area of tree stems, 1.3 m above ground) was 93% (range: 84–99%). The algorithm was used with discrete return ALS point data, but the computation principle also allows delineation of tree crowns in ALS waveform data.     

An object-based temporal inversion approach to urban land use change analysis

Rates of population growth and urbanization currently taking place in sub-Saharan Africa are and will be the highest in the world, providing impetus for remote-sensing-based monitoring of land cover and land use change (LCLUC). The objective of this study is to assess the utility of using segmentation and classification information derived from an object-based classification of an image at a later date (t = 2) to aid in the segmentation and classification of an image at an earlier date (t = 1) for the same area, in the context of a post-classification comparison for LCLUC analysis within Kumasi, Ghana. This object-based temporal inversion approach was found to increase the accuracy of the t = 1 classification and land use change classifications by 6.2% and 6.6%, respectively, compared to a traditional, non-constrained object-based image analysis (OBIA) approach.     

Resolvable estuaries for satellite derived water quality within the continental United States

ABSTRACT

There are a wide range of satellite sensors used for water quality measures with various spatial resolutions. Here, we focus on spatial resolution because some estuaries are smaller than the satellite nadir pixel width, and multiple pixels within an estuary are required for quality assurance . We used the United States Environmental Protection Agency’s (US EPA) Estuarine Data Mapper polygon set to determine the spatial resolution required to reliably image every estuary and sub-estuary in the continental US. Kilometre resolution ocean colour sensors resolve 25% of estuaries and 36% of sub-estuaries with a 3 × 3-pixel grid. The 300 m Ocean and Land Colour Instrument (OLCI) on Sentinel-3 resolves 53% of continental US estuaries with a 3 × 3-pixel grid, and 85% of sub-estuaries. Currently orbiting 30 m resolution land imaging satellites are sufficient to resolve all US sub-estuaries and all estuaries in the Atlantic, 89% in the Gulf of Mexico, and 54% in the Pacific with a 3 × 3-pixel grid. However, 45% of Pacific estuaries cannot be resolved at 30 m resolution, because they have narrow riverine morphology. Our results indicate that a resolution of ≤15 m will be necessary to resolve these narrow riverine estuaries, which is only currently available with commercial satellites.     

Segmentation of cardiac magnetic resonance cine images of single ventricle: including or excluding the accessorial ventricle?

Our aim was to compare two different approaches for segmentation of single ventricle (SV) on cardiac magnetic resonance (CMR) cine images. We retrospectively studied 30 consecutive patients (23 males; aged 27 ± 10 years) with a treated SV who underwent 1.5-T CMR using ECG-triggered axial true-FISP, HASTE and cine true-FISP sequences. We classified patients for visceroatrial situs, cardiac axis orientation, ventricular loop, morphology of SV and position of great arteries. One experienced reader segmented cine images twice, firstly including only the systemic ventricle, secondly including both systemic and accessorial ventricles. Ejection fraction (EF), indexed end-diastolic volume (EDVI), end-systolic volume (ESVI), and stroke volume (SVI) were calculated. Data were presented as medians and interquartile intervals. Four patients presented dextrocardia and one patient mesocardia. Two had situs ambiguus with asplenia and one situs ambiguus with polisplenia. Four patients showed right morphology of the SV and three levo-ventricle loop. We found 14 levo-trasposition of great arteries (TGA), 4 levo-malposition of great arteries (MGA), four dextro-MGA, two dextro-TGA, and one inverted vessel position. When segmenting only the systemic ventricle, EDVI (mL/m²) was 65 (50–91), when segmenting both ventricles 76 (58–110) (P < 0.001); ESVI (mL/m²) was 32 (24–45) and 45 (33–60), respectively (P < 0.001); EF (%) was 49 (43–57) and 33 (24–47), respectively (P = 0.003); SVI (mL/m²) was 34 (17–48) and 33 (24–47) (P = 0.070). The inclusion of the accessorial ventricle in the segmentation of SV produce a biased lower EF showing a very low contribution to the pump function.     

Does ambulance use differ between geographic areas? A survey of ambulance use in sparsely and densely populated areas

Aim

The aim of this study was to analyze possible differences in the use of ambulance service between densely and sparsely populated areas.

Methods

This study was designed as a 2-step consecutive study that included the ambulance service in 4 different areas with different geographical characteristics. A specific questionnaire was distributed to the enrolled ambulance services. Completion of one questionnaire was required for each ambulance mission, that is, 1 per patient, during the study periods.For calculations of P values, geographic area was treated as a 4-graded ordered variable, from the most densely populated to the most sparsely populated (ie, urban-suburban-rural-remote rural area). Statistical tests used were Mann-Whitney U test and Spearman rank statistic, when appropriate. All P values are 2 tailed and considered significant if below .01.

Results

The medical status of the patients in the prehospital care situation was more often severe in the sparsely populated areas. In addition, drugs were more often used in the ambulances in these areas. In the sparsely populated areas, ambulance use was more frequently judged as the appropriate mode of transportation compared with the more densely populated areas.

Conclusions

Our study suggests that the appropriateness of the use of ambulance is not optimal. Furthermore, our data suggest that geographical factors, that is, population density, is related to inappropriate use. Thus, strategies to improve the appropriateness of ambulance use should probably take geographical aspects into consideration.     

Estimation of biophysical parameters in wheat crops in Golestan province using ultra-high resolution images

Due to various factors which impress wheat growth variability, we need short–term monitoring of biophysical parameters using ultra–high resolution images. These provide an ability to monitor crops at the individual plant level. Two flight missions were carried out at altitude of 40 m with a commercial quad copter and a commercial camera. The images were taken before and after tillage over an 8.8 ha field. The 2 cm orthoimages and surface models were generated using photogrammetric software. Then, the image variables including ratio of the blue and green band, ratio of the red and blue band,ratio of the red and green band, plant height were extracted from orthoimages and surface models. Field measurement included the leaf area index, plant height and biomass for 15 plots each of area 1 m × 1 m. Due to a linear relationship between the biophysical parameters and image variables, it was used a multivariate regression model for modelling. The model using the image variables resulted in coefficient of determination (R²) of 0.95 and the lowest error measures (RMSE = 0.24). The results show that ultra–high resolution images can be used for monitoring of biophysical parameters in wheat crops but it is limited for large area.     

Species shade tolerance affects tree basal area growth behaviour in two eucalypt species in thinned and unthinned even-aged monoculture

Individual tree and stand basal area growth were studied in a thinning experiment established over two sites in subtropical eastern Australia. The experiment compared the less shade tolerant species Eucalyptus dunnii with the more shade tolerant Corymbia citriodora var. variegata, both grown in plantation monoculture. Growth was compared over a 2½?3 year period that immediately followed thinning at 5½?7½ years of age. Towards the end of the growth period, tree crown depths and leaf mass per unit area were measured at one site. Crown depth and leaf mass per area of C. citriodora were greater than of E. dunnii, characteristics consistent with a more shade tolerant species. Gross stand basal area growth of E. dunnii was faster than that of C. citriodora. Individual-tree basal area growth behaviour was consistent with inter-tree competition involving asymmetric competition for light. Opening the stand by thinning reduced inter-tree competition to near zero. In unthinned control stands, smaller, more shaded trees of C. citriodora were better able to retain their basal area growth rates than those of E. dunnii in the face of competition. In consequence, the more shade tolerant C. citriodora developed a more evenly spread frequency distribution of tree diameters than less shade tolerant E. dunnii. This would have consequences for the assortment of log sizes that would be available ultimately from monocultures of the two species.     

Award of Imperial Service Order to Norman Lewis

A recent study examined the possible impacts of climate change on 657 Australian eucalypt species in the period to 2085 using species distribution modelling (SDM). The study predicted that ‘within the next 60 years the vast majority of species distributions (91%) across Australia will shrink in size (on average by 51%)’. The purpose of the present paper is to demonstrate some of the strengths and weaknesses of this previous study. Its main strength is that it identifies relatively hot and dry areas of species distributions that may be vulnerable under climate change. Its main weakness is that the individual analyses tend to overestimate the areas of species natural distributions. Consequently, the predicted percentage losses of species distribution areas are unreliable. To illustrate the problem the freely available Atlas of Living Australia (ALA) is used examine two contrasting species (Eucalyptus diversicolor and E. nitens) in detail, so readers will be able to apply similar methods to any eucalypt species of interest. For well-known species a more reliable assessment of likely losses of distributional area under climate change may be obtained by applying the results of the SDM analysis, but assuming that ALA occurrences within 25 km x 25 km areas are an accurate representation of present natural distributions. Using this approach the estimated loss of area of natural distribution by 2085 for both E. diversicolor and E. nitens are less than half the estimates provided by the original paper. For lesser-known species, it is concluded that an additional SDM analysis is required to provide a closer representation of species natural distributions, to which the original SDM climate change results, which attempt to capture some of the species adaptability/plasticity, could be applied.     

Respiratory variations in the photoplethysmographic waveform amplitude depend on type of pulse oximetry device

Respiratory variations in the photoplethysmographic waveform amplitude predict fluid responsiveness under certain conditions. Processing of the photoplethysmographic signal may vary between different devices, and may affect respiratory amplitude variations calculated by the standard formula. The aim of the present analysis was to explore agreement between respiratory amplitude variations calculated using photoplethysmographic waveforms available from two different pulse oximeters. Analysis of registrations before and after fluid loads performed before and after open-heart surgery (aortic valve replacement and/or coronary artery bypass grafting) with patients on controlled mechanical ventilation. Photoplethysmographic (Nellcor and Masimo pulse oximeters) and arterial pressure waveforms were recorded. Amplitude variations induced by ventilation were calculated and averaged over ten respiratory cycles. Agreements for absolute values are presented in scatterplots (with least median square regression through the origin, LMSO) and Bland–Altman plots. Agreement for trending presented in a four-quadrant plot. Agreement between respiratory photoplethysmographic amplitude variations from the two pulse oximeters was poor with LMSO ΔPOP_Nellc = 1.5 × ΔPOP_Mas and bias ± limits of agreement 7.4 ± 23 %. Concordance rate with a fluid load was 91 %. Agreement between respiratory variations in the photoplethysmographic waveform amplitude calculated from the available signals output by two different pulse oximeters was poor, both evaluated by LMSO and Bland–Altman plot. Respiratory amplitude variations from the available signals output by these two pulse oximeters are not interchangeable.     

Automatic segmentation, detection and quantification of coronary artery stenoses on CTA

Accurate detection and quantification of coronary artery stenoses is an essential requirement for treatment planning of patients with suspected coronary artery disease. We present a method to automatically detect and quantify coronary artery stenoses in computed tomography coronary angiography. First, centerlines are extracted using a two-point minimum cost path approach and a subsequent refinement step. The resulting centerlines are used as an initialization for lumen segmentation, performed using graph cuts. Then, the expected diameter of the healthy lumen is estimated by applying robust kernel regression to the coronary artery lumen diameter profile. Finally, stenoses are detected and quantified by computing the difference between estimated and expected diameter profiles. We evaluated our method using the data provided in the Coronary Artery Stenoses Detection and Quantification Evaluation Framework. Using 30 testing datasets, the method achieved a detection sensitivity of 29 % and a positive predictive value (PPV) of 24 % as compared to quantitative coronary angiography (QCA), and a sensitivity of 21 % and a PPV of 23 % as compared manual assessment based on consensus reading of CTA by 3 observers. The stenoses degree was estimated with an absolute average difference of 31 %, a root mean square difference of 39.3 % when compared to QCA, and a weighted kappa value of 0.29 when compared to CTA. A Dice of 68 and 65 % was reported for lumen segmentation of healthy and diseased vessel segments respectively. According to the ranking of the evaluation framework, our method finished fourth for stenosis detection, second for stenosis quantification and second for lumen segmentation.     

Multi-scale segmentation approach for object-based land-cover classification using high-resolution imagery

Image segmentation is a basic and important procedure in object-based classification of remote-sensing data. This study presents an approach to multi-scale optimal segmentation (OS), given that single-scale segmentation may not be the most suitable approach to map a variety of land-cover types characterized by various spatial structures; it objectively measures the appropriate segmentation scale for each object at various scales and projects them onto a single layer. A 1.8 m spatial resolution Worldview-2 image was used to perform successive multi-scale segmentations. The pixel standard deviation of an object was used to measure the optimal scale that occurred on the longest, feature unchanged scale range during multi-scale segmentation. Results indicate that the classification of multi-scale object OS can improve the overall accuracy by five percentage points compared to traditional single segmentation.     

Segmentation of anatomical structures in chest radiographs using supervised methods: a comparative study on a public database

The task of segmenting the lung fields, the heart, and the clavicles in standard posterior-anterior chest radiographs is considered. Three supervised segmentation methods are compared: active shape models, active appearance models and a multi-resolution pixel classification method that employs a multi-scale filter bank of Gaussian derivatives and a k-nearest-neighbors classifier. The methods have been tested on a publicly available database of 247 chest radiographs, in which all objects have been manually segmented by two human observers. A parameter optimization for active shape models is presented, and it is shown that this optimization improves performance significantly. It is demonstrated that the standard active appearance model scheme performs poorly, but large improvements can be obtained by including areas outside the objects into the model. For lung field segmentation, all methods perform well, with pixel classification giving the best results: a paired t-test showed no significant performance difference between pixel classification and an independent human observer. For heart segmentation, all methods perform comparably, but significantly worse than a human observer. Clavicle segmentation is a hard problem for all methods; best results are obtained with active shape models, but human performance is substantially better. In addition, several hybrid systems are investigated. For heart segmentation, where the separate systems perform comparably, significantly better performance can be obtained by combining the results with majority voting. As an application, the cardio-thoracic ratio is computed automatically from the segmentation results. Bland and Altman plots indicate that all methods perform well when compared to the gold standard, with confidence intervals from pixel classification and active appearance modeling very close to those of a human observer. All results, including the manual segmentations, have been made publicly available to facilitate future comparative studies.     

Reproducible Computer-Assisted Quantification of Myocardial Perfusion with Contrast-Enhanced Ultrasound

Myocardial perfusion can be quantified by myocardial contrast echocardiography (MCE) and is used for the diagnosis of coronary artery disease (CAD). However, existing MCE quantification software is highly operator dependent and has poor reproducibility and ease of usage. The aim of this study was to develop robust and easy-to-use software that can perform MCE quantification accurately, reproducibly and rapidly. The developed software has the following features: (i) semi-automatic segmentation of the myocardium; (ii) automatic rejection of MCE data with poor image quality; (iii) automatic computation of perfusion parameters such as myocardial blood flow (MBF). MCE sequences of 18 individuals (9 normal, 9 with CAD) undergoing vasodilator stress with dipyridamole were analysed quantitatively using the software. When evaluated against coronary angiography, the software achieved a sensitivity of 71% and a specificity of 91% for hyperemic MBF. With the automatic rejection algorithm, the sensitivity and specificity further improved to 77% and 94%, respectively. For MBF reproducibility, the percentage agreement is 85% (κ = 0.65) for inter-observer variability and 88% (κ = 0.72) for intra-observer variability. The intra-class correlation coefficients are 0.94 (inter-observer) and 0.96 (intra-observer). The time taken to analyse one MCE sequence using the software is about 3 min on a PC. The software has exhibited good diagnostic performance and reproducibility for CAD detection and is rapid and user-friendly.     

FOLFOX chemotherapy can safely be given to neutropenic patients with early-stage colorectal cancer for higher dose intensity and fewer visits

Purpose

How does giving adjuvant FOLFOX chemotherapy to patients with early-stage colorectal cancer (ESCRC) regardless of the day-before absolute neutrophil counts (ANC) effect chemotherapy-induced febrile neutropenia (CIFN) rates, received dose intensity (RDI), and chemotherapy cycle delay? Does an ANC level predict future neutropenia?

Methods

A retrospective chart review was conducted on all patients receiving adjuvant chemotherapy for ESCRC at a mid-sized community hospital in Toronto, Ontario, Canada between April 2005 and May 2014. All patients were under one medical oncologist. Day-before CBC data were collected along with other patient characteristics. CIFN was confirmed by hospital records. Inclusion criteria were met by 132 patients. Overall, 1074 cycles of chemotherapy were analyzed.

Results

Six episodes of CIFN were observed. There was a significant difference in the average day-before ANC between patients who developed CIFN (1.4 × 10⁹/L, 95 % CI 0.76–2.0 × 10⁹/L) and those who did not (2.9 × 10⁹/L, 95 % CI 2.8–3.0 × 10⁹/L, p = 0.03). The RDI for oxaliplatin was 0.95 and for 5-fluorouracil (5-FU) was 0.96. A total of 170 cycles were given at day-before ANC <1.5 × 10⁹/L (range 0.1 × 10⁹/L–1.4 × 10⁹/L), and 24 were delayed for 1 week for hematologic reasons. Cycles given with grade 2 neutropenia predicted higher grades of neutropenia with a sensitivity of 0.22 (95 % CI 0.12–0.38).

Conclusions

Adjuvant FOLFOX chemotherapy may be given in the setting of low day-before ANC to patients with ESCRC. The benefits include higher RDI and a reduced number of clinic visits for the patient.

     

Diagnostic accuracy of 320-row computed tomography as compared with invasive coronary angiography in unselected, consecutive patients with suspected coronary artery disease

Noninvasive coronary angiography with multislice computed tomography (CT) scanners is feasible with high sensitivity and negative predictive value. The radiation exposure associated with this technique, however, is high and concerns in the widespread use of CT have arisen. We evaluated the diagnostic accuracy of coronary angiography using 320-row CT, which avoids exposure-intensive overscanning and overranging. We prospectively studied 118 unselected consecutive patients with suspected coronary artery disease (CAD) referred for invasive coronary angiography (ICA). All patients had 320-row CT within 1 week of ICA, which, together with quantitative analysis, served as the reference standard. Of the 65 out of 118 patients who were diagnosed as having CAD by ICA, 64 (98 %) were correctly identified at 320-row CT. Noteworthy, 320-row CT correctly detected CAD in 3 patients with atrial fibrillation and ruled out the disease in the other 8 patients. From 151 significant coronary stenoses detected on ICA, 137 (91 %) were correctly identified with 320-row CT. In the per-patient analysis, sensitivity and specificity of 320-row CT were 98 and 91 %, respectively. In the per-vessel analysis, sensitivity and specificity of 320-row CT were 93 and 95 %, respectively. In the per segment analysis, sensitivity and specificity of 320-row CT were 91 and 99 %, respectively. Diameter stenosis determined with the use of CT showed good correlation with ICA (P < 0.001, R = 0.81) without significant underestimation or overestimation (?3.1 ± 24.4 %; P = 0.08). Comparison of CT with ICA revealed a significantly smaller effective radiation dose (3.1 ± 2.3 vs. 6.5 ± 4.2 mSv; P < 0.05) and amount of contrast agent required (99 ± 51 vs. 65 ± 42 ml, P < 0.05) for 320 row CT. The present study in an unselected population including patients with atrial fibrillation demonstrates that 320-row CT may significantly reduce the radiation dose and amount of contrast agent required compared with ICA while maintaining a very high diagnostic accuracy.     

The relationship of CD34+ dosage and platelet recovery following high dose chemotherapy and autologous CD34+ reinfusion in multiple myeloma

Autologous hematopoietic stem cell transplantation (ASCT) is an established treatment for multiple myeloma (MM), yet the impact of transplanted CD34+ cell dose remains unresolved, especially in patients over the age of 65 years. Data was collected from 207 consecutive ASCT patients to determine the relationship between CD34+ infusion count and short-term and long-term platelet recovery. For MM patients under the age of 65 years (n = 155), CD34+ dosage correlates with time to platelet engraftment (p < 0.001) and platelet count at 30 days (p = 0.003), but not with long-term platelet counts at 180 or 360 days from the CD34+ reinfusion. For MM patients aged 65 years or older (n = 46), CD34+ dosage did not correlate with time to platelet engraftment, but did correlate with both short-term and long-term platelet counts at 30 (p < 0.001), 180 (p = 0.021), and 360 days (p = 0.005). Exploratory regression analysis was done to explore platelet stability following the current minimum CD34+ dosage reinfusion. For MM patients under the age of 65 years, the minimum standard CD34+ dosage of 2 × 10⁶ cells/kg was sufficient for a timing to platelet engraftment of <21 days and short-term platelets count ≥150 × 10⁹/L at 30 days. Alternatively, for MM patients aged 65 years or older, the CD34+ dosage of 2 × 10⁶ cells/kg was insufficient for platelet counts ≥150 × 10⁹/L at 30 and only marginally attainable at 360 days suggesting that in elderly MM patients a higher CD34+ dosage may be required for platelet recovery and possibly long-term platelet stability.     

Use of a semi-automated cardiac segmentation tool improves reproducibility and speed of segmentation of contaminated right heart magnetic resonance angiography

Three-dimensional printing has an increasing number of clinical applications in pediatric cardiology. Time required for dataset segmentation and conversion to stereolithography (STL) format remains a significant limitation. We investigated the impact of semi-automated cardiovascular-specific segmentation software on time and reproducibility of segmentation. Magnetic resonance angiograms (MRAs) of 19 patients undergoing intervention for right ventricular outflow lesions were segmented to demonstrate the right heart. STLs were created by two independent clinicians using semi-automated cardiovascular segmentation (SAS) and traditional manual segmentation (MS). Time was recorded and geometric STL disagreement was determined (0?%?=?no disagreement, 100?%?=?complete disagreement). MRA datasets were categorized as clean when only right heart structures were present in the MRA, or contaminated when left heart structures were also present and required removal. Eighteen (seven clean and 11 contaminated) cases were successfully segmented with both methods. Time to STL for clean datasets was faster with MS than SAS [median 209 s (IQR 192–252) vs. 296 s (272–317), p?=?0.018] while contaminated datasets were faster with SAS [455 s (384–561) vs. 866 s (310–1429), p?=?0.033]. Interobserver STL geometric disagreement was significantly lower using SAS than MS overall (0.70?±?1.15?% vs. 1.31?±?1.52?%, p?=?0.030), and for the contaminated subset (0.81?±?1.08?% vs. 1.75?±?1.57?%, p?=?0.036). Most geometric disagreement occurred at areas where left heart contamination was removed. Semi-automated segmentation was faster and more reproducible for contaminated datasets, while MS was faster but equally reproducible for clean datasets. Semi-automated segmentation methods are preferable for contaminated datasets and continued refinement of these tools should be supported.     

Local noise estimation in low-dose chest CT images

Purpose

   Image noise in computed tomography (CT) images may have significant local variation due to tissue properties, dose, and location of the X-ray source. We developed and tested an automated tissue-based estimator method for estimating local noise in CT images.

Method

   An automated TBE method for estimating the local noise in CT image in 3 steps was developed: (1) Partition the image into homogeneous and transition regions, (2) For each pixel in the homogeneous regions, compute the standard deviation in a $15\times 15\times 1$ voxel local region using only pixels from the same homogeneous region, and (3) Interpolate the noise estimate from the homogeneous regions in the transition regions. Noise-aware fat segmentation was implemented. Experiments were conducted on the anthropomorphic phantom and in vivo low-dose chest CT scans to validate the TBE, characterize the magnitude of local noise variation, and determine the sensitivity of noise estimates to the size of the region in which noise is computed. The TBE was tested on all scans from the Early Lung Cancer Action Program public database. The TBE was evaluated quantitatively on the phantom data and qualitatively on the in vivo data.

Results

   The results show that noise can vary locally by over 200 Hounsfield units on low-dose in vivo chest CT scans and that the TBE can characterize these noise variations within 5 %. The new fat segmentation algorithm successfully improved segmentation on all 50 scans tested.

Conclusion

   The TBE provides a means to estimate noise for image quality monitoring, optimization of denoising algorithms, and improvement of segmentation algorithms. The TBE was shown to accurately characterize the large local noise variations that occur due to changes in material, dose, and X-ray source location.     

Fertilization and Crop Residue Addition Impacts on Yield Sustainability Under a Rainfed Maize–Wheat System in the Himalayas

A 9-year old experiment was conducted at Almora, India to study the effects of mineral sources of nutrients in different combinations with or without crop residue or farmyard manure (FYM) addition on crop productivity under a rainfed maize–wheat system. Plots under 100 % nitrogen–phosphorus–potassium (NPK) + FYM had maximum mean maize (5.00 Mg ha^?1) and wheat (2.61 Mg ha^?1) yields that were generally significantly higher than yields observed under other treatments. Total soil organic carbon (C) increased in all treatments except with mineral fertilization and control plots. While NPK treated plots had significantly higher benefit:cost ratio than NPK + FYM plots, organic C content in the NPK treated plots decreased over the initial soil and FYM treated plots had better soil physical and chemical properties than NPK only. Thus, the study showed that although the combined 100 % NPK and FYM application had higher productivity of the maize–wheat system, the same is as remunerative as 50 % NPK + FYM, if the cost of FYM was considered. However, depending upon the resource availability, farmers can also apply Kudzu, maize stalk and wheat straw annually along with adjusted dose of NPK to a crop and full dose of NPK to the other crop as the alternate options.     

Histopathologic Validation of Grayscale Carotid Plaque Characteristics Related to Plaque Vulnerability

Inflammation and angiogenesis play major roles in carotid plaque vulnerability. The purpose of this study was to determine whether gray-scale features of carotid plaques are associated with histologic markers for inflammation. Thirty-eight individuals completed a dedicated research carotid ultrasound exam before carotid endarterectomy. Gray-scale analysis was performed on plaque images to measure plaque echogenicity (gray-scale median [GSM] pixel brightness), plaque area, presence of discrete white areas (DWAs) and the percent of black area near the lumen on any one component of the plaque. Plaques with higher ultrasound GSM had greater percent calcification (p = 0.013) on histopathology. Presence of an ultrasound DWA was associated with more plaque hemosiderin (p = 0.0005) and inflammation (p = 0.019) on histopathology examination. The percent of plaque black area in any one component was associated with a higher score for macroscopic ulceration (p = 0.028). Ultrasound plaque characteristics (GSM, DWAs and black areas) represent histopathologic markers associated with plaque vulnerability. ClinicalTrials.gov identifier: NCT02476396.