AIMC Topic: Deep Learning

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Deep Learning for Neuroimaging Segmentation with a Novel Data Augmentation Strategy.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Brain insults such as cerebral ischemia and intracranial hemorrhage are critical stroke conditions with high mortality rates. Currently, medical image analysis for critical stroke conditions is still largely done manually, which is time-consuming and...

A V-Net Based Deep Learning Model for Segmentation and Classification of Histological Images of Gastric Ablation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Gastric motility disorders are associated with bioelectrical abnormalities in the stomach. Recently, gastric ablation has emerged as a potential therapy to correct gastric dysrhythmias. However, the tissue-level effects of gastric ablation have not y...

Interphase Cell Cycle Staging using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The progression of cells through the cell cycle is a tightly regulated process and is known to be key in maintaining normal tissue architecture and function. Disruption of these orchestrated phases will result in alterations that can lead to many dis...

Combining Deep Learning with Handcrafted Features for Cell Nuclei Segmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Segmentation of cell nuclei in fluorescence microscopy images provides valuable information about the shape and size of the nuclei, its chromatin texture and DNA content. It has many applications such as cell tracking, counting and classification. In...

Deep Learning Model based Ki-67 Index estimation with Automatically Labelled Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Ki-67 labelling index is a biomarker which is used across the world to predict the aggressiveness of cancer. To compute the Ki-67 index, pathologists normally count the tumour nuclei from the slide images manually; hence it is timeconsuming and is su...

Carcino-Net: A Deep Learning Framework for Automated Gleason Grading of Prostate Biopsies.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Gleason scoring for prostate cancer grading is a subjective examination and suffers from suboptimal interobserver and intraobserver variability. To overcome these limitations, we have developed an automated system to grade prostate biopsies. We prese...

Evaluating Deep Learning Algorithms in Pulmonary Nodule Detection.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Lung cancer is considered the deadliest cancer worldwide. In order to detect it, radiologists need to inspect multiple Computed Tomography (CT) scans. This task is tedious and time consuming. In recent years, promising methods based on deep learning ...

Malocclusion Classification on 3D Cone-Beam CT Craniofacial Images Using Multi-Channel Deep Learning Models.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Analyzing and interpreting cone-beam computed tomography (CBCT) images is a complicated and often time-consuming process. In this study, we present two different architectures of multi-channel deep learning (DL) models: "Ensemble" and "Synchronized m...

Volumetric Choroidal Segmentation Using Sequential Deep Learning Approach in High Myopia Subjects.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Many ocular diseases are associated with choroidal changes. Therefore, it is crucial to be able to segment the choroid to study its properties. Previous methods for choroidal segmentation have focused on single cross-sectional scans. Volumetric choro...

MDL-IWS: Multi-view Deep Learning with Iterative Watershed for Pulmonary Fissure Segmentation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Pulmonary fissure segmentation is important for localization of lung lesions which include nodules at respective lobar territories. This can be very useful for diagnosis as well as treatment planning. In this paper, we propose a novel coarse-to-fine ...