AIMC Topic: Image Processing, Computer-Assisted

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MoDL: Model-Based Deep Learning Architecture for Inverse Problems.

IEEE transactions on medical imaging
We introduce a model-based image reconstruction framework with a convolution neural network (CNN)-based regularization prior. The proposed formulation provides a systematic approach for deriving deep architectures for inverse problems with the arbitr...

Identifying epidermal growth factor receptor mutation status in patients with lung adenocarcinoma by three-dimensional convolutional neural networks.

The British journal of radiology
OBJECTIVE:: Genetic phenotype plays a central role in making treatment decisions of lung adenocarcinoma, especially the tyrosine-kinase-inhibitors-sensitive mutations of the epidermal growth factor receptor (EGFR) gene. We constructed three-dimension...

Efficient B-Mode Ultrasound Image Reconstruction From Sub-Sampled RF Data Using Deep Learning.

IEEE transactions on medical imaging
In portable, 3-D, and ultra-fast ultrasound imaging systems, there is an increasing demand for the reconstruction of high-quality images from a limited number of radio-frequency (RF) measurements due to receiver (Rx) or transmit (Xmit) event sub-samp...

Skin lesion classification with ensembles of deep convolutional neural networks.

Journal of biomedical informatics
Skin cancer is a major public health problem with over 123,000 newly diagnosed cases worldwide in every year. Melanoma is the deadliest form of skin cancer, responsible for over 9000 deaths in the United States each year. Thus, reliable automatic mel...

Deep learning applied to whole-brain connectome to determine seizure control after epilepsy surgery.

Epilepsia
OBJECTIVE: We evaluated whether deep learning applied to whole-brain presurgical structural connectomes could be used to predict postoperative seizure outcome more accurately than inference from clinical variables in patients with mesial temporal lob...

Computer-aided detection of small intestinal ulcer and erosion in wireless capsule endoscopy images.

Physics in medicine and biology
A novel computer-aided detection method based on deep learning framework was proposed to detect small intestinal ulcer and erosion in wireless capsule endoscopy (WCE) images. To the best of our knowledge, this is the first time that deep learning fra...

Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images.

NeuroImage
The human cerebellum plays an essential role in motor control, is involved in cognitive function (i.e., attention, working memory, and language), and helps to regulate emotional responses. Quantitative in-vivo assessment of the cerebellum is importan...

Deep Neural Networks for In Situ Hybridization Grid Completion and Clustering.

IEEE/ACM transactions on computational biology and bioinformatics
Transcriptome in brain plays a crucial role in understanding the cortical organization and the development of brain structure and function. Two challenges, incomplete data and high dimensionality of transcriptome, remain unsolved. Here, we present a ...

Deep learning to predict the lab-of-origin of engineered DNA.

Nature communications
Genetic engineering projects are rapidly growing in scale and complexity, driven by new tools to design and construct DNA. There is increasing concern that widened access to these technologies could lead to attempts to construct cells for malicious i...

Fusion of encoder-decoder deep networks improves delineation of multiple nuclear phenotypes.

BMC bioinformatics
BACKGROUND: Nuclear segmentation is an important step for profiling aberrant regions of histology sections. If nuclear segmentation can be resolved, then new biomarkers of nuclear phenotypes and their organization can be predicted for the application...