Automated Multi-Stage Segmentation of White Blood Cells Via Optimizing Color Processing

Segmentation of white blood cells (i.e. leukocytes) is a crucial step toward the development of haematological images analysis of peripheral blood smears due to the complex nature of the different types of white blood cells and their large variations in shape, texture, color, and density. This study addresses this issue and presents a single fully automatic segmentation framework for both nuclei and cytoplasm of the five classes of leukocytes in a microscope blood smears. The proposed framework integrates a priori information of enhanced nuclei color with Gram-Schmidt orthogonalization, and multi-scale morphological enhancement to localize the nuclei, whereas clustering-based seed extraction and watershed are utilized to segment the cytoplasm. The experimental results on two different datasets show that the proposed method works successfully for both nuclei and cytoplasm segmentation, and achieves more accurate segmentation results compared to the other methods in the literature

Segmentasi Sel Bertumpuk pada Citra Mikroskopis Sel Kanker Payudara menggunakan Spatial Fuzzy C-Means Clustering dan Rapid Region Merging

Penerapan teknik pengolahan citra untuk menganalisis citra mikroskopis sel kanker payudara dilakukan untuk mempermudah diagnosis penyakit kanker payudara. Proses pemisahan sel kanker payudara bertumpuk dianggap penting karena hasil pemisahan sel kanker bertumpuk akan mempengaruhi akurasi perhitungan jumlah sel. Keberhasilan proses pemisahan sel bertumpuk juga dipengaruhi oleh proses identifikasi sel, proses deteksi sel bertumpuk dan penanganan masalah over-segmentation. Pemisahan sel kanker menggunakan algoritma clustering pada citra mikroskopis sel darah putih menghasilkan nilai akurasi yang cukup baik. Kombinasi metode Spatial Fuzzy C-means Clustering (SFCM) dan Rapid Region Merging (RRM) untuk pemisahan sel kanker bertumpuk dan penanganan masalah over-segmentation dipaparkan pada penelitian ini. Citra masukan yang digunakan pada tahapan pemisahan sel bertumpuk adalah citra hasil identifikasi sel kanker payudara berdasarkan metode Gram-Schmidt, sedangkan sel kanker yang diproses pada tahapan pemisahan sel kanker bertumpuk adalah sel kanker yang dideteksi bertumpuk berdasarkan informasi fitur geometri area. Berdasarkan hasil pengujian dilakukan terhadap 40 citra mikroskopis jenis benign dan malignant, kombinasi metode SFCM dan RRM memberikan hasil paling baik berdasarkan perolehan nilai rata-rata Mean Square Error (MSE) sebesar 0,07 pada tahapan identifikasi sel dan nilai akurasi pemisahan sel bertumpuk sebesar 78.41% ================================================================= The application of image processing techniques to analyze the microscopic image of the breast cancer cells was done to make the diagnosis of breast cancer easier. The separation process of overlapped breast cancer cells is important because the separation result of overlapped cancer cells will affect the accuracy of cell counting. The success of overlapped cells separation are also affected by cell identification process, overlapped cell detection process and the handling of over-segmentation problems. The separation of cancer cells using clustering algorithm on white blood cells microscopic image produce a fairly good accuracy. The combination of Spatial Fuzzy C-Means (SFCM) and Rapid Region Merging (RRM) method for separating the overlapped cancer cells and handling the over-segmentation problems are presented in this study. The input image used in overlapped cell separation phases is the image from identification result of breast cancer cell by Gram-Schmidt method, where as the overlapped cancer cells that are processed at separation phase is detected by the area information from geomatric features. Based on the evaluation on 40 microscopic image of benign and malignant types, the combinations between SFCM and RRM method provides superior results with average value of Mean Square Error (MSE) is 0,07 on cell identification phase and the accuracy value of overlapped cells separation is 78,41%

Anatomo-functional magnetic resonance imaging of the spinal cord and its application to the characterization of spinal lesions in cats

Les lésions de la moelle épinière ont un impact significatif sur la qualité de la vie car elles peuvent induire des déficits moteurs (paralysie) et sensoriels. Ces déficits évoluent dans le temps à mesure que le système nerveux central se réorganise, en impliquant des mécanismes physiologiques et neurochimiques encore mal connus. L'ampleur de ces déficits ainsi que le processus de réhabilitation dépendent fortement des voies anatomiques qui ont été altérées dans la moelle épinière. Il est donc crucial de pouvoir attester l'intégrité de la matière blanche après une lésion spinale et évaluer quantitativement l'état fonctionnel des neurones spinaux. Un grand intérêt de l'imagerie par résonance magnétique (IRM) est qu'elle permet d'imager de façon non invasive les propriétés fonctionnelles et anatomiques du système nerveux central. Le premier objectif de ce projet de thèse a été de développer l'IRM de diffusion afin d'évaluer l'intégrité des axones de la matière blanche après une lésion médullaire. Le deuxième objectif a été d'évaluer dans quelle mesure l'IRM fonctionnelle permet de mesurer l'activité des neurones de la moelle épinière. Bien que largement appliquées au cerveau, l'IRM de diffusion et l'IRM fonctionnelle de la moelle épinière sont plus problématiques. Les difficultés associées à l'IRM de la moelle épinière relèvent de sa fine géométrie (environ 1 cm de diamètre chez l'humain), de la présence de mouvements d'origine physiologique (cardiaques et respiratoires) et de la présence d'artefacts de susceptibilité magnétique induits par les inhomogénéités de champ, notamment au niveau des disques intervertébraux et des poumons. L'objectif principal de cette thèse a donc été de développer des méthodes permettant de contourner ces difficultés. Ce développement a notamment reposé sur l'optimisation des paramètres d'acquisition d'images anatomiques, d'images pondérées en diffusion et de données fonctionnelles chez le chat et chez l'humain sur un IRM à 3 Tesla. En outre, diverses stratégies ont été étudiées afin de corriger les distorsions d'images induites par les artefacts de susceptibilité magnétique, et une étude a été menée sur la sensibilité et la spécificité de l'IRM fonctionnelle de la moelle épinière. Les résultats de ces études démontrent la faisabilité d'acquérir des images pondérées en diffusion de haute qualité, et d'évaluer l'intégrité de voies spinales spécifiques après lésion complète et partielle. De plus, l'activité des neurones spinaux a pu être détectée par IRM fonctionnelle chez des chats anesthésiés. Bien qu'encourageants, ces résultats mettent en lumière la nécessité de développer davantage ces nouvelles techniques. L'existence d'un outil de neuroimagerie fiable et robuste, capable de confirmer les paramètres cliniques, permettrait d'améliorer le diagnostic et le pronostic chez les patients atteints de lésions médullaires. Un des enjeux majeurs serait de suivre et de valider l'effet de diverses stratégies thérapeutiques. De telles outils représentent un espoir immense pour nombre de personnes souffrant de traumatismes et de maladies neurodégénératives telles que les lésions de la moelle épinière, les tumeurs spinales, la sclérose en plaques et la sclérose latérale amyotrophique.Spinal cord injury has a significant impact on quality of life since it can lead to motor (paralysis) and sensory deficits. These deficits evolve in time as reorganisation of the central nervous system occurs, involving physiological and neurochemical mechanisms that are still not fully understood. Given that both the severity of the deficit and the successful rehabilitation process depend on the anatomical pathways that have been altered in the spinal cord, it may be of great interest to assess white matter integrity after a spinal lesion and to evaluate quantitatively the functional state of spinal neurons. The great potential of magnetic resonance imaging (MRI) lies in its ability to investigate both anatomical and functional properties of the central nervous system non invasively. To address the problem of spinal cord injury, this project aimed to evaluate the benefits of diffusion-weighted MRI to assess the integrity of white matter axons that remain after spinal cord injury. The second objective was to evaluate to what extent functional MRI can measure the activity of neurons in the spinal cord. Although widely applied to the brain, diffusion-weighted MRI and functional MRI of the spinal cord are not straightforward. Various issues arise from the small cross-section width of the cord, the presence of cardiac and respiratory motions, and from magnetic field inhomogeneities in the spinal region. The main purpose of the present thesis was therefore to develop methodologies to circumvent these issues. This development notably focused on the optimization of acquisition parameters to image anatomical, diffusion-weighted and functional data in cats and humans at 3T using standard coils and pulse sequences. Moreover, various strategies to correct for susceptibility-induced distortions were investigated and the sensitivity and specificity in spinal cord functional MRI was studied. As a result, acquisition of high spatial and angular diffusion-weighted images and evaluation of the integrity of specific spinal pathways following spinal cord injury was achieved. Moreover, functional activations in the spinal cord of anaesthetized cats was detected. Although encouraging, these results highlight the need for further technical and methodological development in the near-future. Being able to develop a reliable neuroimaging tool for confirming clinical parameters would improve diagnostic and prognosis. It would also enable to monitor the effect of various therapeutic strategies. This would certainly bring hope to a large number of people suffering from trauma and neurodegenerative diseases such as spinal cord injury, tumours, multiple sclerosis and amyotrophic lateral sclerosis

Functional anatomy of stereoscopic visual process assessed using functional magnetic resonance imaging and structural equation modelling.

The purpose of this thesis is to study the functional anatomy of stereoscopic vision. Although many studies have investigated the physiological mechanisms by which the brain transforms the retinal disparities into three-dimensional representations, the invasive nature of the techniques available have restricted them to studies in non-human primates, whilst the research on humans has been limited to psychophysical studies. Modem non-invasive neuroimaging techniques now allow the investigation of the functional organisation of the human brain. Although PET and fMRI studies have been widely used, few researchers have explored the functional anatomy of stereoscopic vision. Most of these studies appear to be pilot work, showing inconsistency, not only in the areas sensitive to stereo disparities, but also in the specific role that each of these possesses in the perception of depth. In order to investigate the cortical regions involved in stereoscopic vision, four fMRI studies were performed using anaglyph random dot stereo grams. Our results suggest that the stereo disparity processing is widespread over a network of cortical regions which include VI, V3A, V3B and B7. Functionally, the V3A region seems to be the main processing centre of pure stereo disparities and the V3B region to be engaged in motion defined purely by spatio-temporal changes of local horizontal disparities (stereoscopic -cyclopean- motion). Interregional connectivity was investigated with two approaches. Structural Equation Modelling (SEM), as the classical technique for the analysis of effective connectivity, was used to assess one connectivity model proposed to· explain the cortical interaction observed in the first experiment. The implementation and application of this technique permitted us to identify some of its weaknesses in representing fMRI data. An extension of the SEM technique was introduced as a Non-linear Auto-Regressive Moving Average with eXogenous variables (NARMAX) approach. This can be thought of as an attempt to bring SEM towards a non-linear dynamic system modelling technique which permits a more appropriate representation of effective connectivity models using fMRI time series