However, in many cases, gross morphological changes occur in the brain, such as in the development of tumors. Models that deal with such cases are still in their infancy [41, 42]. As a second example, we note the analysis of images from animals whose genetic composition is altered, so ...
Some boundaries in the manual segmentation were defined as planes marked by landmarks; such boundaries showed greater mismatch. In some cases, the proximity of structures with similar intensity distorted the LP results: e.g., parts of the parahippocampal gyrus w...
Class-Guided Image-to-Image Diffusion: Cell Painting from Brightfield Images with Class Labels Jan Oscar Cross-Zamirski, Praveen Anand, Guy Williams, Elizabeth Mouchet, Yinhai Wang, Carola-Bibiane Schönlieb [15th Mar., 2023] [arXiv, 2023] [Paper] [Github]...
However, the representation power of CNNs is still somewhat limited in dealing with challenging image recognition tasks. Take image classification and fine-grained visual categorization (FGVC) as examples, Figures 1(a) and (b) show some example images and their corresponding labels from the PASCAL...
We trained these models on COYO-700M or its subsets from scratch, achieving competitive performance to the reported numbers or generated samples in the original papers. Since this observation supports the high quality of our dataset, we hope it to be continuously updated with open collaboration. ...
The retinal dataset used for training purposes has a relatively small sample size. To address this limitation and enhance the diversity of the training set, various preprocessing techniques are applied to both the images and labels. These techniques include grayscale conversion, flipping, rotation, ho...
Therefore, we explore the analysis of brain images together with survival data to predict survival in gliomas with a focus on improving the interpretability of the results. Using the Brain Tumor Segmentation dataset BraTS 2020, we used a well-validated dataset for evaluation and relied on a ...
It can be seen that the details of the brain tumor are captured well by UNETR (Hatamizadeh et al., 2022b). As opposed to other methods that attempted to utilize the Transformer module as an additional block beside the CNN-based components in the architectures, UNETR (Hatamizadeh et al.,...
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proposed to normalize each modality of each patient independently by subtracting the mean and dividing by the standard deviation of the brain region. 3.3. Data augmentation Most of the time, a large number of labels for training is not available for several reasons. Labelling the dataset requires...