Biomedical Imaging Essay

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Over the past few decades a lot of biomedical information has been gathered (in the form of images, signals and sequences) and there is a great deal of knowledge that can be gathered from the raw data \cite{manyika2011big}. The biomedical imaging data consists of magnetic resonance image (MRI) \cite{edelman1993magnetic, ogawa1990brain}, radiographic image \cite{hsieh2009computed, chapman1997diffraction}, positron emission tomography \cite{bailey2005positron} and others. Biomedical signaling data includes electroencephalography (EEG) \cite{niedermeyer2005electroencephalography}, electrocorticography (ECoG) \cite{buzsaki2012origin}, electrocardiography (ECG) \cite{marriott1988practical} and others. Deep learning, with its rise since the 2000s, …show more content…
Regarding biomedical imaging, DNNs can be used for anomaly classification \cite{plis2013deep, hua2015computer, suk2013deep}, segmentation \cite{li2015cross}, recognition \cite{xu2015stacked} and brain decoding \cite{van2010neural, koyamada2015deep}. Concerning biomedical signal processing we similarly have anomaly classification \cite{huanhuan2014classification, wulsin2011modeling, turner2014deep, zhao2014deep}, brain decoding and emotion classification \cite{freudenburg2011real, an2014deep, li2013affective, jia2014novel, zheng2015revealing}. There is aslso research on patients suffering from schizophrenia \cite{plis2013deep} and Alzheimer’s disease \cite{taigman2014deepface}. One area that can lead to progress is figuring out how to encode raw data to be fed to the networks, so that DNNs can learn features on its own, instead of being provided by the …show more content…
On one hand, deep learning requires large amounts of data \cite{bengio2009learning} and that can provide some challenges: data can have too much noise and that can sometimes very easily lead to wrong conclusions; there are a lot of very rare diseases, which means the sample size will be small and hard to gather knowledge from; some data can even be restricted to parts of the scientific and research communities due to various reasons. Solutions to these problems mostly consist of pre-training \cite{lopez2013insight, erhan2010does, pan2010survey, deng2009imagenet} and advanced training methods \cite{lee2015boosted,

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