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This contribution demonstrates an example of experimental automatic image analysis to detect spores prepared on microscope slides derived from trapping. The application is to monitor aerial spore counts of the entomopathogenic fungus Pandora neoaphidis which may serve as a biological control agent for aphids. Automatic detection of such spores can therefore play a role in plant protection. The present approach for such detection is a modification of traditional manual microscopy of prepared slides, where autonomous image recording precedes computerised image analysis. The purpose of the present image analysis is to support human visual inspection of imagery data - not to replace it. The workflow has three components:•Preparation of slides for microscopy.•Image recording.•Computerised image processing where the initial part is, as usual, segmentation depending on the actual data product. Then comes identification of blobs, calculation of principal axes of blobs, symmetry operations and projection on a three parameter egg shape space.
Evaluation of bone marrow fibrosis and osteosclerosis in myeloproliferative neoplasms (MPN) is subject to interobserver inconsistency. Performance data for currently utilized fibrosis grading systems are lacking, and classification scales for osteosclerosis do not exist. Digital imaging can serve as a quantification method for fibrosis and osteosclerosis. We used digital imaging techniques for trabecular area assessment and reticulin fiber quantification. Patients with all Philadelphia negative MPN subtypes had higher trabecular volume than controls (p
There are numerous systems and techniques to measure the growth of plant roots. However, phenotyping large numbers of plant roots for breeding and genetic analyses remains challenging. One major difficulty is to achieve high throughput and resolution at a reasonable cost per plant sample. Here we describe a cost-effective root phenotyping pipeline, on which we perform time and accuracy benchmarking to identify bottlenecks in such pipelines and strategies for their acceleration.
Ki67 positivity in invasive breast cancers has an inverse correlation with survival outcomes and serves as an immunohistochemical surrogate for molecular subtyping of breast cancer, particularly ER positive breast cancer. The optimal threshold of Ki67 in both settings, however, remains elusive. We use computer assisted image analysis (CAIA) to determine the optimal threshold for Ki67 in predicting survival outcomes and differentiating luminal B from luminal A breast cancers.
Patients with hereditary diffuse gastric cancer often undergo prophylactic gastrectomy to minimize cancer risk. Because intramucosal poorly cohesive carcinomas in this setting are typically not grossly visible, many pathologists assess the entire gastrectomy specimen microscopically. With 150 or more slides per case, this is a major time burden for pathologists. This study utilizes deep learning methods to analyze digitized slides and detect regions of carcinoma.
The purpose of this work is to present a computer assisted diagnostic tool for radiologists in their diagnosis of Alzheimer's disease. A statistical likelihood-ratio procedure from signal detection theory was implemented in the detection of Alzheimer's disease. The probability density functions of the likelihood ratio were constructed by using medial temporal lobe (MTL) volumes of patients with Alzheimer's disease (AD) and normal controls (NC). The volumes of MTL as well as other anatomical regions of the brains were calculated by the FreeSurfer software using T1 weighted MRI images. The MRI images of AD and NC were downloaded from the database of Alzheimer's disease neuroimaging initiative (ADNI). A separate dataset of minimal interval resonance imaging in Alzheimer's disease (MIRIAD) was used for diagnostic testing. A sensitivity of 89.1% and specificity of 87.0% were achieved for the MIRIAD dataset which are better than the 85% sensitivity and specificity achieved by the best radiologists without input of other patient information.
Quantitative evaluation of mosaics of photoreceptors and neurons is essential in studies on development, aging and degeneration of the retina. Manual counting of samples is a time consuming procedure while attempts to automatization are subject to various restrictions from biological and preparation variability leading to both over- and underestimation of cell numbers. Here we present an adaptive algorithm to overcome many of these problems.Digital micrographs were obtained from cone photoreceptor mosaics visualized by anti-opsin immuno-cytochemistry in retinal wholemounts from a variety of mammalian species including primates. Segmentation of photoreceptors (from background, debris, blood vessels, other cell types) was performed by a procedure based on Rudin-Osher-Fatemi total variation (TV) denoising. Once 3 parameters are manually adjusted based on a sample, similarly structured images can be batch processed. The module is implemented in MATLAB and fully documented online.
This study was designed to evaluate the use of computer-assisted navigation with computed tomography (CT) images for bone reconstruction after resection in malignant bone tumor treatment. Forty-five patients with malignant bone tumors were recruited for this study. CT scan images in a computer-assisted navigation system were used to assist during the osteotomy, the pairing with allografts, and the monitoring of the allograft and joint lines to perform joint reconstruction. Our results show that osteotomy and allograft pairing were successful in all patients. The average duration of the osteotomy procedures was 46.8±12.3 min; and the average pairing time was 32.5±9.8 min. The anatomical registration points and the three-dimensional virtual CT images were successfully matched. The average error of registration was 0.36±0.09 mm. Also, the range of tumor resection and allograft osteotomy were successfully paired, with an average error of 0.11±0.03 mm. No complications such as unequal limbs length or joint deformities occurred after reconstruction. The average follow-up time was 11.6±3.9 months. The tumor recurrence rate was 11.1% (5/45) and the survival rate 95.6% (43/45). The average healing time for the allograft and host bone was 5.5±1.2 months and no unexpected internal fixations, fractures or joint collapses occurred. The average knee joint functionality MSTS score was 25.5±6.6 points. No significant differences were found in the length of tumor resection, rate of negative incision margin, duration of osteotomy or of pairing, registration error or allogeneic bone and defect matching error averages between those patients with tumor recurrence and those without it (p>0.05). Based on our results, the computer-assisted navigation system for bone reconstruction after malignant tumor resection allows for high precision during osteotomy, delivers a high success rate of pairing, results in great limb function and low complication rates, and is thus a highly successful and safe approach benefiting bone cancer patients.
Conventional image-guided neurosurgery relies on preoperative images to provide surgical navigational information and visualization. However, these images are no longer accurate once the skull has been opened and brain shift occurs. To account for changes in the shape of the brain caused by mechanical (e.g., gravity-induced deformations) and physiological effects (e.g., hyperosmotic drug-induced shrinking, or edema-induced swelling), updated images of the brain must be provided to the neuronavigation system in a timely manner for practical use in the operating room. In this paper, a novel preoperative and intraoperative computational processing pipeline for near real-time brain shift correction in the operating room was developed to automate and simplify the processing steps. Preoperatively, a computer model of the patient's brain with a subsequent atlas of potential deformations due to surgery is generated from diagnostic image volumes. In the case of interim gross changes between diagnosis, and surgery when reimaging is necessary, our preoperative pipeline can be generated within one day of surgery. Intraoperatively, sparse data measuring the cortical brain surface is collected using an optically tracked portable laser range scanner. These data are then used to guide an inverse modeling framework whereby full volumetric brain deformations are reconstructed from precomputed atlas solutions to rapidly match intraoperative cortical surface shift measurements. Once complete, the volumetric displacement field is used to update, i.e., deform, preoperative brain images to their intraoperative shifted state. In this paper, five surgical cases were analyzed with respect to the computational pipeline and workflow timing. With respect to postcortical surface data acquisition, the approximate execution time was 4.5 min. The total update process which included positioning the scanner, data acquisition, inverse model processing, and image deforming was ~11-13 min. In addition, easily implemented hardware, software, and workflow processes were identified for improved performance in the near future.
The number and spatial configuration of the screws will affect the stability and prognosis of the fractures. In our study, we assessed the biomechanical effects of the double-head cannulated compression screw (DhCCS) and ordinary cannulated compression screw (OCCS) for the treatment of femoral neck fractures by using computer finite element analysis. The original digital imaging and communications in medicine (DICOM)data of a proximal femur were imported into Materialise's interactive medical image control system (MIMICS)software for modeling. Both DhCCS and OCCS 3D-models were obtained by using the 3D scan technique. Using the fracture model and internal fixation assembly model with an inverted triangle, two horizontal and vertical distribution were established in UG software. Next, the displacement and stress distribution were calculated in ANSYS software. The displacement value of the femoral head in the DhCCS group was smaller than that in the OCCS group, and the displacement value in the two horizontal groups was smaller than that in the vertical group. The stress distribution in the DhCCS group was concentrated on the screw rod at the fracture block and thread end, while only at the fracture block in the OCCS group. The stress in the horizontal group was more dispersed on the screws than that in the vertical group. DhCCS has reliable stability for the fixation of femoral neck fractures and applied in the clinical work and 2 horizontal fixation can be used when two screws are selected.
The ability to measure minute structural changes in neural circuits is essential for long-term in vivo imaging studies. Here, we propose a methodology for detection and measurement of structural changes in axonal boutons imaged with time-lapse two-photon laser scanning microscopy (2PLSM). Correlative 2PLSM and 3D electron microscopy (EM) analysis, performed in mouse barrel cortex, showed that the proposed method has low fractions of false positive/negative bouton detections (2/0 out of 18), and that 2PLSM-based bouton weights are correlated with their volumes measured in EM (r = 0.93). Next, the method was applied to a set of axons imaged in quick succession to characterize measurement uncertainty. The results were used to construct a statistical model in which bouton addition, elimination, and size changes are described probabilistically, rather than being treated as deterministic events. Finally, we demonstrate that the model can be used to quantify significant structural changes in boutons in long-term imaging experiments.
Surgical 5/6 nephrectomy and adenine-induced kidney failure in rats are frequently used models of progressive renal failure. In both models, rats develop significant morphological changes in the kidneys and quantification of these changes can be used to measure the efficacy of prophylactic or therapeutic approaches. In this study, the Aperio Genie Pattern Recognition technology, along with the Positive Pixel Count, Nuclear and Rare Event algorithms were used to quantify histological changes in both rat renal failure models.
Iliosacral screw insertion by computer-assisted navigation gradually became the main technique in some hospitals, but the expensive price limited the extensive application. But other techniques such as 3D printed template was used to place iliosacral screw as novel method. This study was to compare the efficiency of percutaneous iliosacral screw placement by using patient-specific template and computer-assisted navigation.
The cortical bone trajectory (CBT) screw technique yields effective mechanical and clinical results, improving the holding screw strength with a less invasive exposure. Accurate and safe screw placement is crucial. A patient-specific drill template with a preplanned trajectory was considered a promising solution; however, it is critical to assess the efficacy and safety of this technique. This study aims to evaluate the accuracy of patient-specific computed tomography (CT)-based rapid prototype drill guide templates for the CBT technique. CT scanning was performed in 7 cadaveric thoracolumbar spines, and a 3-dimensional reconstruction model was generated. By using computer software, we constructed drill templates that fit onto the posterior surface of thoracolumbar vertebrae with drill guides to match the CBT. In total, 80 guide templates from T11 to L5 were created from the computer models by using rapid prototyping. The drill templates were used to guide the drilling of CBT screws without any fluoroscopic control, and CT images were obtained after fixation. The entry point and direction of the planned and inserted screws were measured and compared. In total, 80 screws were inserted from T11 to L5. No misplacement or bony perforation was observed on postoperative CT scan. The patient-specific prototype template system showed the advantage of safe and accurate cortical screw placement in the thoracolumbar spine. This method showed its ability to customize the patient-specific trajectory of the spine, based on the unique morphology of the spine. The potential use of drill templates to place CBT screws is promising.
Collagen fibers play an important role in tumor initiation, progression, and invasion. Our previous research has already shown that large-scale tumor-associated collagen signatures (TACS) are powerful prognostic biomarkers independent of clinicopathological factors in invasive breast cancer. However, they are observed on a macroscale and are more suitable for identifying high-risk patients. It is necessary to investigate the effect of the corresponding microscopic features of TACS so as to more accurately and comprehensively predict the prognosis of breast cancer patients.
A strong association between functional bladder disorders and bladder sensation is well-known, with a relationship between malfunctioning detrusor muscle and abnormal sensation arising from the sub-urothelium and the lamina propria (LP), has been suggested. However, the exact underlying pathophysiology of these bladder disorders is not completely understood. Therefore, it is important to gain knowledge on sensory innervation of the urinary bladder in order to understand the neural network function in healthy and diseased bladder. In the present study we aim at the development of a computer-assisted method for 3D-tracking of sensory innervation in the murine bladder mucosa using two-photon laser scanning microscopy (TPLSM). TPLSM was performed on 10 fixed, stained (CGRP) bladder samples in both the trigone and dome. Nerve tracking was performed in subvolumes (6.3±2.9106μm3; median±IQR) of 22 stacks with determining total nerve length, nerve segment lengths, curviness, straightness, and locations of branching and ending points in the lamina propria (LP). The results show that the highest concentration of afferent fibres was found at the urothelium-LP interface. Nerve curviness, a presumed indicator of nerve activity, showed an equal value throughout the complete LP. We found a significantly higher median nerve segment length in the LP of the trigone and significantly more curved nerves in the dome of the bladder. This indicates an adaptation to, or an involvement in the detection of, bladder volume changes. Conclusively, we successfully developed a computer-assisted method for 3D tracking of sensory nerve fibres in the LP of the murine bladder wall.
The analysis of microcircuitry (the connectivity at the level of individual neuronal processes and synapses), which is indispensable for our understanding of brain function, is based on serial transmission electron microscopy (TEM) or one of its modern variants. Due to technical limitations, most previous studies that used serial TEM recorded relatively small stacks of individual neurons. As a result, our knowledge of microcircuitry in any nervous system is very limited. We applied the software package TrakEM2 to reconstruct neuronal microcircuitry from TEM sections of a small brain, the early larval brain of Drosophila melanogaster. TrakEM2 enables us to embed the analysis of the TEM image volumes at the microcircuit level into a light microscopically derived neuro-anatomical framework, by registering confocal stacks containing sparsely labeled neural structures with the TEM image volume. We imaged two sets of serial TEM sections of the Drosophila first instar larval brain neuropile and one ventral nerve cord segment, and here report our first results pertaining to Drosophila brain microcircuitry. Terminal neurites fall into a small number of generic classes termed globular, varicose, axiform, and dendritiform. Globular and varicose neurites have large diameter segments that carry almost exclusively presynaptic sites. Dendritiform neurites are thin, highly branched processes that are almost exclusively postsynaptic. Due to the high branching density of dendritiform fibers and the fact that synapses are polyadic, neurites are highly interconnected even within small neuropile volumes. We describe the network motifs most frequently encountered in the Drosophila neuropile. Our study introduces an approach towards a comprehensive anatomical reconstruction of neuronal microcircuitry and delivers microcircuitry comparisons between vertebrate and insect neuropile.
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