Visual criteria for diagnosing diffused liver diseases from ultrasound images can be assisted by computerized tissue classification. Feature extraction algorithms are proposed in this paper to extract the tissue characterization parameters from liver images. The resulting parameter set is further processed to obtain the minimum number of parameters which represent the most discriminating pattern space for classification. This preprocessing step has been applied to over 120 distinct pathology-investigated cases to obtain the learning data for classification. The extracted features are divided into independent training and test sets, and are used to develop and compare both statistical and neural classifiers. The optimal criteria for these classifiers are set to have minimum classification error, ease of implementation and learning, and the flexibility for future modifications. Various algorithms of classification based on statistical and neural network methods are presented and tested. The authors show that very good diagnostic rates can be obtained using unconventional classifiers trained on actual patient data.

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In this study, we aim to demonstrate the fate of allogenic adult human olfactory bulb neural stem/progenitor cells (OBNSC/NPCs) transplanted into the rat hippocampus treated with ibotenic acid (IBO), a neurotoxicant specific to hippocampal cholinergic neurons that are lost in Alzheimer's disease. We assessed their possible ability to survive, integrate, proliferate, and differentiate into different neuronal and glial elements: we also evaluate their possible therapeutic potential, and the mechanism(s) relevant to neuroprotection following their engraftment into the CNS milieu. OBNSC/NPCs were isolated from adult human olfactory bulb patients, genetically engineered to express GFP and human nerve growth factor (hNGF) by lentivirus-mediated infection, and stereotaxically transplanted into the hippocampus of IBO-treated animals and controls. Stereological analysis of engrafted OBNSCs eight weeks post transplantation revealed a 1.89 fold increase with respect to the initial cell population, indicating a marked ability for survival and proliferation. In addition, 54.71 ± 11.38%, 30.18 ± 6.00%, and 15.09 ± 5.38% of engrafted OBNSCs were identified by morphological criteria suggestive of mature neurons, oligodendrocytes and astrocytes respectively. Taken together, this work demonstrated that human OBNSCs expressing NGF ameliorate the cognitive deficiencies associated with IBO-induced lesions in AD model rats, and the improvement can probably be attributed primarily to neuronal and glial cell replacement as well as the trophic influence exerted by the secreted NGF.

Mesenchymal stem cells (MSCs) are multipotent cells that can differentiate into various cell types such as cartilage, bone, and fat cells. Recent studies have shown that induction of MSCs in vitro by growth factors including epidermal growth factor (EGF) and fibroblast growth factor (FGF2) causes them to differentiate into neural like cells. These cultures also express ChAT, a cholinergic marker; and TH, a dopaminergic marker for neural cells. To establish a protocol with maximum differentiation potential, we examined MSCs under three experimental culture conditions using neural induction media containing FGF2, EGF, BMP-9, retinoic acid, and heparin. Adipose-derived MSCs were extracted and expanded in vitro for 3 passages after reaching >80% confluency, for a total duration of 9 days. Cells were then characterized by flow cytometry for CD markers as CD44 positive and CD45 negative. MSCs were then treated with neural induction media and were characterized by morphological changes and Q-PCR. Differentiated MSCs expressed markers for immature and mature neurons; β Tubulin III (TUBB3) and MAP2, respectively, showing the neural potential of these cells to differentiate into functional neurons. Improved protocols for MSCs induction will facilitate and ensure the reproducibility and standard production of MSCs for therapeutic applications in neurodegenerative diseases.