Color and morphological features extraction and nuclei classification in tissue samples of colorectal cancer

Cancer is an important public health problem and the third most leading cause of death in North America. Among the highest impact types of cancer are colorectal, breast, lung, and prostate. This thesis addresses the features extraction by using different artificial intelligence algorithms that provide distinct solutions for the purpose of Computer-AidedDiagnosis (CAD). For example, classification algorithms are employed in identifying histological structures, such as lymphocytes, cancer-cells nuclei and glands, from features like existence, extension or shape. The morphological aspect of these structures indicates the degree of severity of the related disease. In this paper, we use a large dataset of 5000 images to classify eight different tissue types in the case of colorectal cancer. We compare results with another dataset. We perform image segmentation and extract statistical information about the area, perimeter, circularity, eccentricity and solidity of the interest points in the image. Finally, we use and compare four popular machine learning techniques, i.e., Naive Bayes, Random Forest, Support Vector Machine and Multilayer Perceptron to classify and to improve the precision of category assignation. The performance of each algorithm was measured using 3 types of metrics: Precision, recall and F1-Score representing a huge contribution to the existing literature complementing it in a quantitative way. The large number of images has helped us to circumvent the overfitting and reproducibility problems. The main contribution is the use of new characteristics different from those already studied, this work researches about the color and morphological characteristics in the images that may be useful for performing tissue classification in colorectal cancer histology

An overview of artificial intelligence and robotics. Volume 1: Artificial intelligence. Part B: Applications

Artificial Intelligence (AI) is an emerging technology that has recently attracted considerable attention. Many applications are now under development. This report, Part B of a three part report on AI, presents overviews of the key application areas: Expert Systems, Computer Vision, Natural Language Processing, Speech Interfaces, and Problem Solving and Planning. The basic approaches to such systems, the state-of-the-art, existing systems and future trends and expectations are covered

Automated recognition of cell phenotypes in histology images based on membrane- and nuclei-targeting biomarkers

<p>Abstract</p> <p>Background</p> <p>Three-dimensional <it>in vitro </it>culture of cancer cells are used to predict the effects of prospective anti-cancer drugs <it>in vivo</it>. In this study, we present an automated image analysis protocol for detailed morphological protein marker profiling of tumoroid cross section images.</p> <p>Methods</p> <p>Histologic cross sections of breast tumoroids developed in co-culture suspensions of breast cancer cell lines, stained for E-cadherin and progesterone receptor, were digitized and pixels in these images were classified into five categories using <it>k</it>-means clustering. Automated segmentation was used to identify image regions composed of cells expressing a given biomarker. Synthesized images were created to check the accuracy of the image processing system.</p> <p>Results</p> <p>Accuracy of automated segmentation was over 95% in identifying regions of interest in synthesized images. Image analysis of adjacent histology slides stained, respectively, for Ecad and PR, accurately predicted regions of different cell phenotypes. Image analysis of tumoroid cross sections from different tumoroids obtained under the same co-culture conditions indicated the variation of cellular composition from one tumoroid to another. Variations in the compositions of cross sections obtained from the same tumoroid were established by parallel analysis of Ecad and PR-stained cross section images.</p> <p>Conclusion</p> <p>Proposed image analysis methods offer standardized high throughput profiling of molecular anatomy of tumoroids based on both membrane and nuclei markers that is suitable to rapid large scale investigations of anti-cancer compounds for drug development.</p

Aerospace Medicine and Biology. A continuing bibliography with indexes

This bibliography lists 244 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1981. Aerospace medicine and aerobiology topics are included. Listings for physiological factors, astronaut performance, control theory, artificial intelligence, and cybernetics are included

Emerging Auditory Selectivity in the Caudomedial Neostriatum of the Zebra Finch Songbird

The ability to identify and interpret auditory stimuli from the environmental milieu is of particular importance in species that communicate using learned vocalizations. By chronically recording multiunit neuronal responses in awake, behaving zebra finch songbirds, I have demonstrated that the caudomedial neostriatum (NCM), a telencephalic nucleus in the ascending auditory pathway, exhibits responses that range from unselective to highly selective for species-specific stimuli. Sites demonstrating habituating responses are also found and are arranged heterogeneously with selective sites that do not habituate. During the act of singing, activity changes at the habituating sites becoming nonhabituating with neuronal firing occurring at distinct points in the song. Together, these data suggest the involvement of NCM in the processing of behaviorally significant stimuli both for passive audition and for auditory feedback

ZIPRO1: Fine Tuning Proliferation in Discrete Cell Populations

Zipro 1 a zinc finger transcnption factor that has a restricted pattern of expression in several tissues. The main cells expressing Ziprol are proliferating cells from epidermal lineages. This includes the cerebellar granule cells (GCs), nasal epithelia and dermal papilla. Through gene dosage experiments we have shown that Ziprol is involved in proliferation GCs, Hair follicles and the Cranio-facial process. Overexpression of Ziprol results an increase in the number of G C s , this increase in G C s directly regulates the appearance of secondary fissure in the cerebellum. Overexpression also results in follicular dysplasia caused by an increase in cells within dermal papilla. Ziprol null mutants show a restricted phenotype of decreases in proliferation in the cranio-facial process. To understand h o w Ziprol effects these changes it is necessary to know which genes Ziprol regulates. Using gene arrays we have found a gene, which is regulated by Ziprol this gene, is the Ski oncogene. The regulation can be seen in the Ziprol \u27~, which show deficits in Ski expression in the cranio-facial process. This coupled with database searches of genomic sequences using the consensus Ziprol binding site (ZBS) has shown us Ski promotor region contains 2 such sites. Using a transciption assay utilizing a Secreated Alkaline Phosphotase (pSEAP sytem from Clontech) it was shown that transciption from the Ski promotor is dependant on the presence of Ziprol. Also transcription from this promotor under the control of Ziprol is highly context dependant In M C F 7 (human breast cancer) under in Fetal Calf serum the Ski promoter is activated, in N I H 3T3 cells the Ski promoter cannot be activated by Ziprol. Deletion of the 2 Z B S abolishes transcnption. The reason for the specificity has been shown to be the presence of SDF-lalpha in the Fetal Bovine Media this serum factor is downregulated in adulthood. SDF-lalpha modulates Ziprol activity through a phosphorylation dependant modulation of SUMOlaytion . This study has shown a role for Ziprol acts as a rheostat that is available to adjust the numbers of cells in highly proliferative populations

Size constancy in bat biosonar?

Perception and encoding of object size is an important feature of sensory systems. In the visual system object size is encoded by the visual angle (visual aperture) on the retina, but the aperture depends on the distance of the object. As object distance is not unambiguously encoded in the visual system, higher computational mechanisms are needed. This phenomenon is termed "size constancy". It is assumed to reflect an automatic re-scaling of visual aperture with perceived object distance. Recently, it was found that in echolocating bats, the 'sonar aperture', i.e., the range of angles from which sound is reflected from an object back to the bat, is unambiguously perceived and neurally encoded. Moreover, it is well known that object distance is accurately perceived and explicitly encoded in bat sonar. Here, we addressed size constancy in bat biosonar, recruiting virtual-object techniques. Bats of the species Phyllostomus discolor learned to discriminate two simple virtual objects that only differed in sonar aperture. Upon successful discrimination, test trials were randomly interspersed using virtual objects that differed in both aperture and distance. It was tested whether the bats spontaneously assigned absolute width information to these objects by combining distance and aperture. The results showed that while the isolated perceptual cues encoding object width, aperture, and distance were all perceptually well resolved by the bats, the animals did not assign absolute width information to the test objects. This lack of sonar size constancy may result from the bats relying on different modalities to extract size information at different distances. Alternatively, it is conceivable that familiarity with a behaviorally relevant, conspicuous object is required for sonar size constancy, as it has been argued for visual size constancy. Based on the current data, it appears that size constancy is not necessarily an essential feature of sonar perception in bats