Figure 1
The increased availability and usage of modern medical imaging induced a strong need for automatic medical image segmentation. In this Software article, Müller & Kramer introduce the open-source Python library MIScnn. The framework enables researchers to rapidly set up a complete medical image segmentation pipeline by using just a few lines of code.
Figure 1
Saood and Hatem investigate two structurally-different deep learning techniques, SegNet and U-NET, for semantically segmenting COVID-19 infected tissue regions in CT lung images. They propose that the computer-based techniques may prove as reliable detectors for infected tissue in lung CT scans.
Figure 1 (adapted)
Hirano et al focus on three representative deep neural network-based medical image classification tasks and investigate their vulnerability to the seven model architectures of universal adversarial perturbations.
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BMC Medical Imaging welcomes submissions to this new collection focusing on deepening the understanding of artificial intelligence in medical imaging, highlighting its versatility and applications, and breaking down barriers that still exist in the field.
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In preparation for Earth Day on 22nd April, the BMC Series presents a focus issue on Our Changing Environment, highlighting research from across the journals on climate change, conservation, pollution, and the impact of environmental changes on human health and disease.
With the 28th of February marking World Rare Diseases day, the BMC Series this month looks at highlighting research on the Rare diseases that together affect around 10% of the population. Read the full collection of articles here.
Speed
60 days to first decision for reviewed manuscripts only
41 days to first decision for all manuscripts
141 days from submission to acceptance
17 days from acceptance to publication
Citation Impact
1.792 - 2-year Impact Factor
2.168 - 5-year Impact Factor
0.939 - Source Normalized Impact per Paper (SNIP)
0.598 - SCImago Journal Rank (SJR)
Usage
389,270 Downloads
132 Altmetric mentions
