AIMC Topic: Image Interpretation, Computer-Assisted

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SMBFT: A Modified Fuzzy -Means Algorithm for Superpixel Generation.

Computational and mathematical methods in medicine
Most traditional superpixel segmentation methods used binary logic to generate superpixels for natural images. When these methods are used for images with significantly fuzzy characteristics, the boundary pixels sometimes cannot be correctly classifi...

Few-Shot Breast Cancer Metastases Classification via Unsupervised Cell Ranking.

IEEE/ACM transactions on computational biology and bioinformatics
Tumor metastases detection is of great importance for the treatment of breast cancer patients. Various CNN (convolutional neural network) based methods get excellent performance in object detection/segmentation. However, the detection of metastases i...

MedFuseNet: An attention-based multimodal deep learning model for visual question answering in the medical domain.

Scientific reports
Medical images are difficult to comprehend for a person without expertise. The scarcity of medical practitioners across the globe often face the issue of physical and mental fatigue due to the high number of cases, inducing human errors during the di...

Deep Learning for Automated Triaging of 4581 Breast MRI Examinations from the DENSE Trial.

Radiology
Background Supplemental screening with MRI has proved beneficial in women with extremely dense breasts. Most MRI examinations show normal anatomic and physiologic variation that may not require radiologic review. Thus, ways to triage these normal MRI...

Segmentation of Overlapping Cervical Cells with Mask Region Convolutional Neural Network.

Computational and mathematical methods in medicine
The task of segmenting cytoplasm in cytology images is one of the most challenging tasks in cervix cytological analysis due to the presence of fuzzy and highly overlapping cells. Deep learning-based diagnostic technology has proven to be effective in...

Outcome-based multiobjective optimization of lymphoma radiation therapy plans.

The British journal of radiology
At its core, radiation therapy (RT) requires balancing therapeutic effects against risk of adverse events in cancer survivors. The radiation oncologist weighs numerous disease and patient-level factors when considering the expected risk-benefit ratio...

Diagnostic test accuracy of artificial intelligence analysis of cross-sectional imaging in pulmonary hypertension: a systematic literature review.

The British journal of radiology
OBJECTIVES: To undertake the first systematic review examining the performance of artificial intelligence (AI) applied to cross-sectional imaging for the diagnosis of acquired pulmonary arterial hypertension (PAH).

An automated liver segmentation in liver iron concentration map using fuzzy c-means clustering combined with anatomical landmark data.

BMC medical imaging
BACKGROUND: To estimate median liver iron concentration (LIC) calculated from magnetic resonance imaging, excluded vessels of the liver parenchyma region were defined manually. Previous works proposed the automated method for excluding vessels from t...

A Novel Medical Image Denoising Method Based on Conditional Generative Adversarial Network.

Computational and mathematical methods in medicine
Medical image quality is highly relative to clinical diagnosis and treatment, leading to a popular research topic of medical image denoising. Image denoising based on deep learning methods has attracted considerable attention owing to its excellent a...

Deep learning from MRI-derived labels enables automatic brain tissue classification on human brain CT.

NeuroImage
Automatic methods for feature extraction, volumetry, and morphometric analysis in clinical neuroscience typically operate on images obtained with magnetic resonance (MR) imaging equipment. Although CT scans are less expensive to acquire and more wide...