Using machine learning to speed up manual image annotation: application to a 3D imaging protocol for measuring single cell gene expression in the developing C. elegans embryo

<p>Abstract</p> <p>Background</p> <p>Image analysis is an essential component in many biological experiments that study gene expression, cell cycle progression, and protein localization. A protocol for tracking the expression of individual <it>C. elegans </it>genes was developed that collects image samples of a developing embryo by 3-D time lapse microscopy. In this protocol, a program called StarryNite performs the automatic recognition of fluorescently labeled cells and traces their lineage. However, due to the amount of noise present in the data and due to the challenges introduced by increasing number of cells in later stages of development, this program is not error free. In the current version, the error correction (<it>i.e</it>., editing) is performed manually using a graphical interface tool named AceTree, which is specifically developed for this task. For a single experiment, this manual annotation task takes several hours.</p> <p>Results</p> <p>In this paper, we reduce the time required to correct errors made by StarryNite. We target one of the most frequent error types (movements annotated as divisions) and train a support vector machine (SVM) classifier to decide whether a division call made by StarryNite is correct or not. We show, via cross-validation experiments on several benchmark data sets, that the SVM successfully identifies this type of error significantly. A new version of StarryNite that includes the trained SVM classifier is available at <url>http://starrynite.sourceforge.net</url>.</p> <p>Conclusions</p> <p>We demonstrate the utility of a machine learning approach to error annotation for StarryNite. In the process, we also provide some general methodologies for developing and validating a classifier with respect to a given pattern recognition task.</p

Automatic Extraction of Nuclei Centroids of Mouse Embryonic Cells from Fluorescence Microscopy Images

Accurate identification of cell nuclei and their tracking using three dimensional (3D) microscopic images is a demanding task in many biological studies. Manual identification of nuclei centroids from images is an error-prone task, sometimes impossible to accomplish due to low contrast and the presence of noise. Nonetheless, only a few methods are available for 3D bioimaging applications, which sharply contrast with 2D analysis, where many methods already exist. In addition, most methods essentially adopt segmentation for which a reliable solution is still unknown, especially for 3D bio-images having juxtaposed cells. In this work, we propose a new method that can directly extract nuclei centroids from fluorescence microscopy images. This method involves three steps: (i) Pre-processing, (ii) Local enhancement, and (iii) Centroid extraction. The first step includes two variations: first variation (Variant-1) uses the whole 3D pre-processed image, whereas the second one (Variant-2) modifies the preprocessed image to the candidate regions or the candidate hybrid image for further processing. At the second step, a multiscale cube filtering is employed in order to locally enhance the pre-processed image. Centroid extraction in the third step consists of three stages. In Stage-1, we compute a local characteristic ratio at every voxel and extract local maxima regions as candidate centroids using a ratio threshold. Stage-2 processing removes spurious centroids from Stage-1 results by analyzing shapes of intensity profiles from the enhanced image. An iterative procedure based on the nearest neighborhood principle is then proposed to combine if there are fragmented nuclei. Both qualitative and quantitative analyses on a set of 100 images of 3D mouse embryo are performed. Investigations reveal a promising achievement of the technique presented in terms of average sensitivity and precision (i.e., 88.04% and 91.30% for Variant-1; 86.19% and 95.00% for Variant-2), when compared with an existing method (86.06% and 90.11%), originally developed for analyzing C. elegans images

The role of input materials in shallow seismogenic slip and forearc plateau development: International Ocean Discovery Program Expedition 362 Preliminary Report Sumatra Seismogenic Zone

Drilling the input materials of the north Sumatran subduction zone, part of the 5000 km long Sunda subduction zone system and the origin of the Mw ∼9.2 earthquake and tsunami that devastated coastal communities around the Indian Ocean in 2004, was designed to groundtruth the material properties causing unexpectedly shallow seismogenic slip and a distinctive forearc prism structure. The intriguing seismogenic behavior and forearc structure are not well explained by existing models or by relationships observed at margins where seismogenic slip typically occurs farther landward. The input materials of the north Sumatran subduction zone are a distinctively thick (as thick as 4-5 km) succession of primarily Bengal-Nicobar Fan-related sediments. The correspondence between the 2004 rupture location and the overlying prism plateau, as well as evidence for a strengthened input section, suggest the input materials are key to driving the distinctive slip behavior and long-term forearc structure. During Expedition 362, two sites on the Indian oceanic plate ∼250 km southwest of the subduction zone, Sites U1480 and U1481, were drilled, cored, and logged to a maximum depth of 1500 meters below seafloor. The succession of sediment/rocks that will develop into the plate boundary detachment and will drive growth of the forearc were sampled, and their progressive mechanical, frictional, and hydrogeological property evolution will be analyzed through postcruise experimental and modeling studies. Large penetration depths with good core recovery and successful wireline logging in the challenging submarine fan materials will enable evaluation of the role of thick sedimentar y subduction zone input sections in driving shallow slip and amplifying earthquake and tsunami magnitudes, at the Sunda subduction zone and globally at other subduction zones where submarine fan-influenced sections are being subducted

A Review on Automatic Analysis of Human Embryo Microscope Images

Over the last 30 years the process of in vitro fertilisation (IVF) has evolved considerably, yet the efficiency of this treatment remains relatively poor. The principal challenge faced by doctors and embryologists is the identification of the embryo with the greatest potential for producing a child. Current methods of embryo viability assessment provide only a rough guide to potential. In order to improve the odds of a successful pregnancy it is typical to transfer more than one embryo to the uterus. However, this often results in multiple pregnancies (twins, triplets, etc), which are associated with significantly elevated risks of serious complications. If embryo viability could be assessed more accurately, it would be possible to transfer fewer embryos without negatively impacting IVF pregnancy rates. In order to assist with the identification of viable embryos, several scoring systems based on morphological criteria have been developed. However, these mostly rely on a subjective visual analysis. Automated assessment of morphological features offers the possibility of more accurate quantification of key embryo characteristics and elimination of inter- and intra-observer variation. In this paper, we describe the main embryo scoring systems currently in use and review related works on embryo image analysis that could lead to an automatic and precise grading of embryo quality. We summarise achievements, discuss challenges ahead, and point to some possible future directions in this research field

Systolic, Diastolic and Mean Arterial Pressure at 30-33 Weeks in the Prediction of Preeclampsia

International audienceA holistic view of the Bengal–Nicobar Fan system requires sampling the full sedimentary section of the Nicobar Fan, which was achieved for the first time by International Ocean Discovery Program (IODP) Expedition 362 west of North Sumatra. We identified a distinct rise in sediment accumulation rate (SAR) beginning ∼9.5 Ma and reaching 250–350 m/Myr in the 9.5–2 Ma interval, which equal or far exceed rates on the Bengal Fan at similar latitudes. This marked rise in SAR and a constant Himalayan-derived provenance necessitates a major restructuring of sediment routing in the Bengal–Nicobar submarine fan. This coincides with the inversion of the Eastern Himalayan Shillong Plateau and encroachment of the west-propagating Indo–Burmese wedge, which reduced continental accommodation space and increased sediment supply directly to the fan. Our results challenge a commonly held view that changes in sediment flux seen in the Bengal–Nicobar submarine fan were caused by discrete tectonic or climatic events acting on the Himalayan–Tibetan Plateau. Instead, an interplay of tectonic and climatic processes caused the fan system to develop by punctuated changes rather than gradual progradation