Chromosome karyotyping is a critical way to diagnose various hematological malignancies and genetic diseases,of which chromosome detection in raw metaphase cell images is the most critical and challenging *** this wor...
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Chromosome karyotyping is a critical way to diagnose various hematological malignancies and genetic diseases,of which chromosome detection in raw metaphase cell images is the most critical and challenging *** this work,focusing on the joint optimization of chromosome localization and classification,we propose ChromTR to accurately detect and classify 24 classes of chromosomes in raw metaphase cell *** incorporates semantic feature learning and class distribution learning into a unified DETR-based detection ***,we first propose a Semantic Feature Learning Network(SFLN)for semantic feature extraction and chromosome foreground region segmentation with object-wise ***,we construct a Semantic-Aware Transformer(SAT)with two parallel encoders and a Semantic-Aware decoder to integrate global visual and semantic *** provide a prediction with a precise chromosome number and category distribution,a Category Distribution Reasoning Module(CDRM)is built for foreground-background objects and chromosome class distribution *** evaluate ChromTR on 1404 newly collected R-band metaphase images and the public G-band dataset *** proposed ChromTR outperforms all previous chromosome detection methods with an average precision of 92.56%in R-band chromosome detection,surpassing the baseline method by 3.02%.In a clinical test,ChromTR is also confident in tackling normal and numerically abnormal *** extended to the chromosome enumeration task,ChromTR also demonstrates state-of-the-art performances on R-band and G-band two metaphase image *** these superior performances to other methods,our proposed method has been applied to assist clinical karyotype diagnosis.
Automated tongue image segmentation in tongue diagnosis system of traditional Chinese medicine is difficult due to two factors: There are lots of pathological details on the surface of tongue, and the shapes of tongue...
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In this paper, a face recognition method using local qualitative representations is proposed to solve the problem of face recognition in varying lighting. Based on the observation that the ordinal relationship between...
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ISBN:
(纸本)9780819469526
In this paper, a face recognition method using local qualitative representations is proposed to solve the problem of face recognition in varying lighting. Based on the observation that the ordinal relationship between the average brightness of image regions pair is invariant under lighting changes, Local Binary Mapping is defined as an illumination invariant for face recognition based on Local Binary pattern descriptor, which extracts the local variance features of an image. For the 'symbol' feature vector, hamming distance is used as similarity measurement. It has been proved that the proposed method can provide the accuracy of 100 percent for subset 2, 3, 4 and 98.89 percent for subset 5 of the Yale facial database B when all images in subset 1 are used as gallery.
In automatic image annotation, it is often extracting low-level visual features from original image for the purpose of mapping to high level image semantic information. In this paper, we propose a novel method which i...
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This paper presents a copy-paste block detection method based on characteristics of double JPEG compress. The JPEG compress will bring JPEG compression characteristics to the DCT coefficients, these characteristics ar...
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Two medieval manuscripts are recorded, investigated and analyzed by philologists in collaboration with computer scientists. Due to mold, air humidity and water the parchment is partially damaged and consequently hard ...
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Two medieval manuscripts are recorded, investigated and analyzed by philologists in collaboration with computer scientists. Due to mold, air humidity and water the parchment is partially damaged and consequently hard to read. In order to enhance the readability of the text, the manuscript pages are imaged in different spectral bands ranging from 360 to 1000nm. A registration process is necessary for further imageprocessing methods which combine the information gained by the different spectral bands. Therefore, the images are coarsely aligned using rotationally invariant features and an affine transformation. Afterwards, the similarity of the different images is computed by means of the normalized cross correlation. Finally, the images are accurately mapped to each other by the local weighted mean transformation. The algorithms used for the registration and results in enhancing the texts using Multivariate Spatial Correlation are presented in this paper. copyright by EURASIP.
Multivariate calibration is a classic problem in the analytical chemistry field and frequently solved by partial least squares method in the previous work. Unfortunately there are so many redundant features in the pro...
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In classification of multispectral remote sensing image, it is usually difficult to obtain higher classification accuracy if only consider image's spectral feature or texture feature alone. In this paper ,we prese...
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The safety operation of steel cable is vital and the cable should be maintained through regular inspection. Magnetic flux leakage (MFL) method is a popular inspection technique. For the online nondestructive testing (...
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In order to preserve our cultural heritage and for automated document processing libraries and national archives have started digitizing historical documents. In the case of degraded manuscripts (e.g. by mold, humidit...
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