vincentRoca

Hi, I’m a computer science student and I do my internship in a medical imaging laboratory where I work on machine learning methods for predicting brain age from T1 MRI. I learn every day different things about medical imaging, but I’m still very novice in this field. In a paper, authors talk about “smoothing MRI with a FWHM kernel of 8mm and resampling with spatial resolution of 8mm”. I understand that they apply a gaussian filter and they reduce MRI resolution, but I have two unanswered questions : How do we reduce MRI resolution ? Is it correct to do this simply by using mean operator among neighbors ? That what they mean by saying “resampling” ? Is it better to apply gaussian kernel before or after the resampling/reduction ? Thanks in advance.

Hi, My question is pretty simple : If we center the outputs of our training set on 0 in a regression task by substracting the mean, do we need to use a bias parameter ? I ask this question because I'm using a Sparse Group Lasso model and I don't know how to introduce a bias parameter in it. Thanks in advance

After having done researches, I precise regions for which I'm not sure or I have no idea : Paracentral lobule and sulcus Subcentral gyrus (central operculum) and sulci Lateral occipito-temporal gyrus (fusiform gyrus, O4-T4) Horizontal ramus of the anterior segment of the lateral sulcus (or fissure) Vertical ramus of the anterior segment of the lateral sulcus (or fissure) Posterior ramus (or segment) of the lateral sulcus (or fissure) Central sulcus (Rolando’s fissure) Anterior transverse collateral sulcus Posterior transverse collateral sulcus Medial occipito-temporal sulcus (collateral sulcus) and lingual sulcus Parieto-occipital sulcus (or fissure) Pericallosal sulcus (S of corpus callosum) Subparietal sulcus

Hi, I’m a computer science student and I do my internship in a medical imaging laboratory where I work on machine learning methods for predicting brain age from T1 MRI. I learn every day different things about medical imaging, but I’m still very novice in this field. I wanted to know if there is a simple way to match each anatomical parcellation label (Destrieux atlas https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2937159/table/T1/?report=objectonly) with the correct lobe (frontal, temporal, limbic, parietal, occipital, insula or others). For example, I guess that S_temporal_inf matches with temporal lobe. I hope I will not be forced to make researches for each of the 74 parcellations, especially since I don’t know anything about it and I will not be capable of doing that. My only prior knowledge is on the number of parcellations per lobe : frontal : 19 temporal : 15 limbic : 8 parietal : 10 occipital : 10 insula : 8 others : 4 Any advice, or explanation may really help me in this task, because I don't know anything about it. Thanks in advance for your help.