Gray matter segmented views of the brain. by Muhammad Zubair (728141)

“…The proposed methodology consists of a four-phase process: (1) Whole brain segmentation, (2) Gray matter segmentation using multi-layer U-Net segmentation, (3) Feature extraction using Multi-Scale Efficient Net with SVM for classification, and (4) XAI (explainable AI) techniques by integrating Saliency Map Quantitative Analysis for increased clinical trustworthiness and model interpretability. …”

ECoG timescales decrease during spatial attention. by Isabel Raposo (21615517)

Conditional ablation of <i>Ybx1</i> leads to a reduction in cortical progenitor cell pool and a decrease in cortical thickness. by Jian Zhang (1682)

(A) Auxiliary marking points to ensure complete and accurate seating of the prosthesis. by Long Li (6555)

EVs from infected neurons alter astrocyte gene expression and decrease GLT-1 protein expression. by Emily Z. Tabaie (16630841)

Biases in larger populations. by Sander W. Keemink (21253563)

“…<p>(<b>A</b>) Maximum absolute bias vs the number of neurons in the population for the Bayesian decoder. …”

IKK KO in microglia leads to increased accumulation of PK-resistant PrP <i>in vitro</i> but decreased accumulation <i>in vivo.</i> by Arielle J. D. Hay (15456341)

Cinacalcet administered early in the inactive phase markedly decrease parathyroid Ki-67 index. by Søren Egstrand (10906087)

Proposed Multi-Layer U-Net model for gray matter segmentation. by Muhammad Zubair (728141)

Gray matter segmentation results using the Attention U-Net model. by Muhammad Zubair (728141)

Statins resulted in smaller neuronal soma size. by Shuk C. Tsoi (21192243)

“…Areas of cell somas in the heterogeneous BrdU-/Hu+ group are significantly smaller in the statin-treated (light blue line) group compared to soma areas in controls (dark blue line, bottom panel). Statin treatment decreased cell sizes in the larger cells more than in the smaller cells as seen in the greater divergence between lines plotted for larger cell somas (bottom panel). …”

Conditional knockout of SLAMF5 in CX3CR1^er cells attenuates EAE progression, reduces brain myeloid cell activation, and decreases T cell infiltration. by Laura Bellassen (22209109)

Brain regions with significantly decreased activations for the Raven task are shown in blue. by Morteza Fattahi (15892028)

Gray Matter segmentation results using the proposed Multi-layer U-Net Model. by Muhammad Zubair (728141)

Table 1_Dietary fiber intake and hippocampal gray matter volume: an exploratory cross-sectional study in healthy adults.docx by Raghav Pallapothu (21547964)

“…Prior research has found that ADRD is associated with decreases in cortical gray matter volume (GMV) in the hippocampus.…”

Group-level narrow- and broad-band spectral changes after hemispherotomy reveal a marked EEG slowing of the isolated cortex, robust across patients. by Michele Angelo Colombo (22446342)

“…This decrease was larger in the disconnected than in the contralateral cortex. …”

Data Sheet 1_Changes in voxel-wise gray matter asymmetry over time.pdf by Florian Kurth (350282)

“…However, there is no consensus on whether asymmetries become weaker or stronger with age or which brain regions are most affected. Here, we set out to further explore age-related changes in brain asymmetry, with a particular focus on voxel-wise gray matter asymmetry. …”

Visual comparison of Brain segmentation results. by Muhammad Zubair (728141)

“…The proposed methodology consists of a four-phase process: (1) Whole brain segmentation, (2) Gray matter segmentation using multi-layer U-Net segmentation, (3) Feature extraction using Multi-Scale Efficient Net with SVM for classification, and (4) XAI (explainable AI) techniques by integrating Saliency Map Quantitative Analysis for increased clinical trustworthiness and model interpretability. …”

Toxoplasma infection leads to a decrease in the concentration of EVs. by Emily Z. Tabaie (16630841)

Original 2D MRI views of the brain. by Muhammad Zubair (728141)

“…The proposed methodology consists of a four-phase process: (1) Whole brain segmentation, (2) Gray matter segmentation using multi-layer U-Net segmentation, (3) Feature extraction using Multi-Scale Efficient Net with SVM for classification, and (4) XAI (explainable AI) techniques by integrating Saliency Map Quantitative Analysis for increased clinical trustworthiness and model interpretability. …”