Self-supervised learning approaches leverage unlabeled samples to acquire generic knowledge about different concepts, hence allowing for annotation-efficient downstream task learning. In this paper, we propose a novel self-supervised method that leverages multiple imaging modalities. We introduce the multimodal puzzle task, which facilitates representation from image The learned modality-agnost...

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texture image analysis is one of the most important working realms of imageprocessing in medical sciences and industry. up to present, different approacheshave been proposed for segmentation of texture images. in this paper, we offeredunsupervised texture image segmentation based on markov random field (mrf)model. first, we used gabor filter with different parameters’ (frequency,orientation) va...

background: body image reflects how a person thinks and feels about his/her own body. negative body image results in low self-esteem and depression. the aim of the present study was to investigate the relationship of body image and self-esteem with marital adjustment among female married employees of kerman university of medical sciences. methods: this cross-sectional study was performed on 380...

Many image segmentation techniques are available in the literature. Among the available techniques, parametric deformable models play an important role in many medical imaging applications. These models have been proved to be effective in segmenting an anatomic structure using constraints derived from the image data along with a prior knowledge about the location, size and shape of these struct...

background: role of information source, perceived benefits and risks, and destination image has significantly been examined in travel and tourism literature; however, in medical tourism it is yet to be examined thoroughly. the concept discussed in this article is drawn form well established models in tourism literature. methods: the purpose of this research was to identify the source of informa...