Enhanced Target Detection in Medical Imaging

We built an AI that’s way better at finding targets in medical images, just by teaching

it how to pay attention. Manually segmenting medical images takes experts a ton of time and isn't always

perfect. Existing AI models are good, but they often waste resources on irrelevant

background information. So we created CBAM-Unet++. We took a solid architecture, Unet++,

and added a lightweight "CBAM" attention module. This module helps the network learn

what to focus on and what to ignore, using both channel and spatial attention to pinpoint the

target. The result is a more targeted and accurate model that can find what it’s

looking for with less distraction.