Dual energy subtraction: principles and clinical applications

Two technical solutions using single or dual shot offer different advantages and disadvantages for dual energy subtraction. The principles of these are explained and the main clinical applications with results are demonstrated. Elimination of overlaying bone and proof or exclusion of calcification are the primary aims of energy subtraction chest radiography, offering unique information in different clinical situations.

Multi-sensor background subtraction by fusing multiple region-based probabilistic classifiers

In the recent years, the computer vision community has shown great interest on depth-based applications thanks to the performance and flexibility of the new generation of RGB-D imagery. In this paper, we present an efficient background subtraction algorithm based on the fusion of multiple region-based classifiers that processes depth and color data provided by RGB-D cameras. Foreground objects are detected by combining a region-based foreground prediction (based on depth data) with different background models (based on a Mixture of Gaussian algorithm) providing color and depth descriptions of the scene at pixel and region level. The information given by these modules is fused in a mixture of experts fashion to improve the foreground detection accuracy. The main contributions of the paper are the region-based models of both background and foreground, built from the depth and color data. The obtained results using different database sequences demonstrate that the proposed approach leads to a higher detection accuracy with respect to existing state-of-the-art techniques.

Subtraction hybridization identifies a transformation progression-associated gene PEG-3 with sequence homology to a growth arrest and DNA damage-inducible gene

Cancer is a progressive multigenic disorder characterized by defined changes in the transformed phenotype that culminates in metastatic disease. Determining the molecular basis of progression should lead to new opportunities for improved diagnostic and therapeutic modalities. Through the use of subtraction hybridization, a gene associated with transformation progression in virus- and oncogene-transformed rat embryo cells, progression elevated gene-3 (PEG-3), has been cloned. PEG-3 shares significant nucleotide and amino acid sequence homology with the hamster growth arrest and DNA damage-inducible gene gadd34 and a homologous murine gene, MyD116, that is induced during induction of terminal differentiation by interleukin-6 in murine myeloid leukemia cells. PEG-3 expression is elevated in rodent cells displaying a progressed-transformed phenotype and in rodent cells transformed by various oncogenes, including Ha-ras, v-src, mutant type 5 adenovirus (Ad5), and human papilloma virus type 18. The PEG-3 gene is transcriptionally activated in rodent cells, as is gadd34 and MyD116, after treatment with DNA damaging agents, including methyl methanesulfonate and γ-irradiation. In contrast, only PEG-3 is transcriptionally active in rodent cells displaying a progressed phenotype. Although transfection of PEG-3 into normal and Ad5-transformed cells only marginally suppresses colony formation, stable overexpression of PEG-3 in Ad5-transformed rat embryo cells elicits the progression phenotype. These results indicate that PEG-3 is a new member of the gadd and MyD gene family with similar yet distinct properties and this gene may directly contribute to the transformation progression phenotype. Moreover, these studies support the hypothesis that constitutive expression of a DNA damage response may mediate cancer progression.

Reciprocal subtraction differential RNA display: An efficient and rapid procedure for isolating differentially expressed gene sequences

A reciprocal subtraction differential RNA display (RSDD) approach has been developed that permits the rapid and efficient identification and cloning of both abundant and rare differentially expressed genes. RSDD comprises reciprocal subtraction of cDNA libraries followed by differential RNA display. The RSDD strategy was applied to analyze the gene expression alterations resulting during cancer progression as adenovirus-transformed rodent cells developed an aggressive transformed state, as documented by elevated anchorage-independence and enhanced in vivo oncogenesis in nude mice. This approach resulted in the identification and cloning of both known and a high proportion (>65%) of unknown sequences, including cDNAs displaying elevated expression as a function of progression (progression-elevated gene) and cDNAs displaying suppressed expression as a function of progression (progression-suppressed gene). Sixteen differentially expressed genes, including five unknown progression-elevated genes and six unknown progression-suppressed genes, have been characterized. The RSDD scheme should find wide application for the effective detection and isolation of differentially expressed genes.

Identification of sample-specific sequences in mammalian cDNA and genomic DNA by the novel ligation-mediated subtraction (Limes)

The representational difference analysis (RDA) and other subtraction techniques are used to enrich sample-specific sequences by elimination of ubiquitous sequences existing in both the sample of interest (tester) and the subtraction partner (driver). While applying the RDA to genomic DNA of cutaneous lymphoma cells in order to identify tumor relevant alterations, we predominantly isolated repetitive sequences and artificial repeat-mediated fusion products of otherwise independent PCR fragments (PCR hybrids). Since these products severely interfered with the isolation of tester-specific fragments, we developed a considerably more robust and efficient approach, termed ligation-mediated subtraction (Limes). In first applications of Limes, genomic sequences and/or transcripts of genes involved in the regulation of transcription, such as transforming growth factor β stimulated clone 22 related gene (TSC-22R), cell death and cytokine production (caspase-1) or antigen presentation (HLA class II sequences), were found to be completely absent in a cutaneous lymphoma line. On the assumption that mutations in tumor-relevant genes can affect their transcription pattern, a protocol was developed and successfully applied that allows the identification of such sequences. Due to these results, Limes may substitute/supplement other subtraction/comparison techniques such as RDA or DNA microarray techniques in a variety of different research fields.

Use of cDNA subtraction and RNA interference screens in combination reveals genes required for germ-line development in Caenorhabditis elegans

Caenorhabditis elegans is an ideal organism for the study of the molecular basis of fundamental biological processes such as germ-line development, especially because of availability of the whole genome sequence and applicability of the RNA interference (RNAi) technique. To identify genes involved in germ-line development, we produced subtracted cDNA pools either enriched for or deprived of the cDNAs from germ-line tissues. We then performed differential hybridization on the high-density cDNA grid, on which about 7,600 nonoverlapping expressed sequence tag (EST) clones were spotted, to identify a set of genes specifically expressed in the germ line. One hundred and sixty-eight clones were then tested with the RNAi technique. Of these, 15 clones showed sterility with a variety of defects in germ-line development. Seven of them led to the production of unfertilized eggs, because of defects in spermatogenesis (4 clones), or defects in the oocytes (3 clones). The other 8 clones led to failure of oogenesis. These failures were caused by germ-line proliferation defect (Glp phenotype), meiotic arrest, and defects in sperm–oocyte switch (Mog phenotype) among others. These results demonstrate the efficacy of the screening strategy using the EST library combined with the RNAi technique in C. elegans.

Overview of the most prevalent hypothalamus-specific mRNAs, as identified by directional tag PCR subtraction.

We applied the directional tag PCR subtractive hybridization method to construct a rat hypothalamic cDNA library from which cerebellar and hippocampal sequences had been depleted, enriching 20-30-fold for sequences expressed selectively in the hypothalamus. We studied a sample of 94 clones selected for enrichment in the subtracted library. These clones corresponded to 43 distinct mRNA species, about half of which were novel. Thirty-eight of these 43 mRNAs (corresponding to 85 of the clones in the sample) exhibited enrichment in the hypothalamus; 23 were highly enriched. In situ hybridization studies revealed that one novel species was restricted to cells in a small bilaterally symmetric area of the paraventricular hypothalamus. Other novel mRNAs showed substantial enrichment in basal diencephalic structures, particularly the hypothalamus, without restriction to single hypothalamic nuclei. The data suggest that the hypothalamus utilizes at least two distinct strategies for employing its selectively expressed proteins. Secretory neuropeptides utilized for intercellular communication are produced by functionally discrete nuclei, while several other proteins are shared by structures that are unrelated in their physiological roles but may share biochemical systems.

Toddler subtraction with large sets: further evidence for an analog-magnitude representation of number

Two experiments were conducted to test the hypothesis that toddlers have access to an analog-magnitude number representation that supports numerical reasoning about relatively large numbers. Three-year-olds were presented with subtraction problems in which initial set size and proportions subtracted were systematically varied. Two sets of cookies were presented and then covered The experimenter visibly subtracted cookies from the hidden sets, and the children were asked to choose which of the resulting sets had more. In Experiment 1, performance was above chance when high proportions of objects (3 versus 6) were subtracted from large sets (of 9) and for the subset of older participants (older than 3 years, 5 months; n = 15), performance was also above chance when high proportions (10 versus 20) were subtracted from the very large sets (of 30). In Experiment 2, which was conducted exclusively with older 3-year-olds and incorporated an important methodological control, the pattern of results for the subtraction tasks was replicated In both experiments, success on the tasks was not related to counting ability. The results of these experiments support the hypothesis that young children have access to an analog-magnitude system for representing large approximate quantities, as performance on these subtraction tasks showed a Webers Law signature, and was independent of conventional number knowledge.

Dark Object Subtraction

Resources created at the University of Southampton for the module Remote Sensing for Earth Observation

Vacant parking area estimation through background subtraction and transience map analysis

A method for estimating the dimensions of non-delimited free parking areas by using a static surveillance camera is proposed. The proposed method is specially designed to tackle the main challenges of urban scenarios (multiple moving objects, outdoor illumination conditions and occlusions between vehicles) with no training. The core of this work is the temporal analysis of the video frames to detect the occupancy variation of the parking areas. Two techniques are combined: background subtraction using a mixture of Gaussians to detect and track vehicles and the creation of a transience map to detect the parking and leaving of vehicles. The authors demonstrate that the proposed method yields satisfactory estimates on three real scenarios while being a low computational cost solution that can be applied in any kind of parking area covered by a single camera.

Likelihood-maximising frameworks for enhanced in-car speech recognition

Speech recognition in car environments has been identified as a valuable means for reducing driver distraction when operating non-critical in-car systems. Likelihood-maximising (LIMA) frameworks optimise speech enhancement algorithms based on recognised state sequences rather than traditional signal-level criteria such as maximising signal-to-noise ratio. Previously presented LIMA frameworks require calibration utterances to generate optimised enhancement parameters which are used for all subsequent utterances. Sub-optimal recognition performance occurs in noise conditions which are significantly different from that present during the calibration session - a serious problem in rapidly changing noise environments. We propose a dialog-based design which allows regular optimisation iterations in order to track the changing noise conditions. Experiments using Mel-filterbank spectral subtraction are performed to determine the optimisation requirements for vehicular environments and show that minimal optimisation assists real-time operation with improved speech recognition accuracy. It is also shown that the proposed design is able to provide improved recognition performance over frameworks incorporating a calibration session.

Chinese young children’s strategies on basic addition facts

Kindergartens in China offer structured full-day programs for children aged 3-6. Although formal schooling does not commence until age 7, the mathematics program in kindergartens is specifically focused on developing young children’s facility with simple addition and subtraction. This study explored young Chinese children’s strategies for solving basic addition facts as well as their intuitive understanding of addition via interview methods. Results indicate a strong impact that teacher-directed teaching methods have on young children’s cognitions in relation to addition.

Accurate silhouette segmentation using motion detection and graph cuts

Acquiring accurate silhouettes has many applications in computer vision. This is usually done through motion detection, or a simple background subtraction under highly controlled environments (i.e. chroma-key backgrounds). Lighting and contrast issues in typical outdoor or office environments make accurate segmentation very difficult in these scenes. In this paper, gradients are used in conjunction with intensity and colour to provide a robust segmentation of motion, after which graph cuts are utilised to refine the segmentation. The results presented using the ETISEO database demonstrate that an improved segmentation is achieved through the combined use of motion detection and graph cuts, particularly in complex scenes.

Robust speech recognition using speech enhancement

Automatic Speech Recognition (ASR) has matured into a technology which is becoming more common in our everyday lives, and is emerging as a necessity to minimise driver distraction when operating in-car systems such as navigation and infotainment. In “noise-free” environments, word recognition performance of these systems has been shown to approach 100%, however this performance degrades rapidly as the level of background noise is increased. Speech enhancement is a popular method for making ASR systems more ro- bust. Single-channel spectral subtraction was originally designed to improve hu- man speech intelligibility and many attempts have been made to optimise this algorithm in terms of signal-based metrics such as maximised Signal-to-Noise Ratio (SNR) or minimised speech distortion. Such metrics are used to assess en- hancement performance for intelligibility not speech recognition, therefore mak- ing them sub-optimal ASR applications. This research investigates two methods for closely coupling subtractive-type enhancement algorithms with ASR: (a) a computationally-efficient Mel-filterbank noise subtraction technique based on likelihood-maximisation (LIMA), and (b) in- troducing phase spectrum information to enable spectral subtraction in the com- plex frequency domain. Likelihood-maximisation uses gradient-descent to optimise parameters of the enhancement algorithm to best fit the acoustic speech model given a word se- quence known a priori. Whilst this technique is shown to improve the ASR word accuracy performance, it is also identified to be particularly sensitive to non-noise mismatches between the training and testing data. Phase information has long been ignored in spectral subtraction as it is deemed to have little effect on human intelligibility. In this work it is shown that phase information is important in obtaining highly accurate estimates of clean speech magnitudes which are typically used in ASR feature extraction. Phase Estimation via Delay Projection is proposed based on the stationarity of sinusoidal signals, and demonstrates the potential to produce improvements in ASR word accuracy in a wide range of SNR. Throughout the dissertation, consideration is given to practical implemen- tation in vehicular environments which resulted in two novel contributions – a LIMA framework which takes advantage of the grounding procedure common to speech dialogue systems, and a resource-saving formulation of frequency-domain spectral subtraction for realisation in field-programmable gate array hardware. The techniques proposed in this dissertation were evaluated using the Aus- tralian English In-Car Speech Corpus which was collected as part of this work. This database is the first of its kind within Australia and captures real in-car speech of 50 native Australian speakers in seven driving conditions common to Australian environments.

The effect of dialect mismatch on likelihood-maximising speech enhancement for noise-robust speech recognition

Traditional speech enhancement methods optimise signal-level criteria such as signal-to-noise ratio, but these approaches are sub-optimal for noise-robust speech recognition. Likelihood-maximising (LIMA) frameworks are an alternative that optimise parameters of enhancement algorithms based on state sequences generated for utterances with known transcriptions. Previous reports of LIMA frameworks have shown significant promise for improving speech recognition accuracies under additive background noise for a range of speech enhancement techniques. In this paper we discuss the drawbacks of the LIMA approach when multiple layers of acoustic mismatch are present – namely background noise and speaker accent. Experimentation using LIMA-based Mel-filterbank noise subtraction on American and Australian English in-car speech databases supports this discussion, demonstrating that inferior speech recognition performance occurs when a second layer of mismatch is seen during evaluation.