Endoscopy is a widely used clinical procedure for the early detection of cancers in hollow-organs such as nasopharyngeal cancer, esophageal adenocarcinoma, gastric cancer,colorectal cancer, and bladder cancer. Accurate and temporally consistent localization andsegmentation of diseased region-of-interests enable precise quantification and mapping oflesions from clinical endoscopy videos which is critical for monitoring and surgical planning.
The medical segmentation model is to classify category to diseased region-of-interests inthe input image，it can be classified into many categories, including BE, cancer, HGD, polyp and suspicious.
Libmedicalsegmentation is a segmentation lib which can be used in segmentation of multi-class diseases in endoscopy. It offers simple interfaces for developer to deploysegmentation task on Xilinx FPGA. The following is an example of medical segmentation, where the goal is to mark the diseased region.
The following is an example of semantic segmentation, where the goal is to predict class labels for each pixel in the image.
The following table shows the medical segmentation model supported by the AI Library.
| No | Model Name | Framework |
|---|---|---|
| 1 | FPN_Res18_Medical_segmentation | Caffe |