I created segmentation models using non-contrast CT images and built from scratch without using NVIDIA models.
To understand AH-NET, I studied model accuracy differences with the same parameters except for setting pre-training weight, but when I re-evaluated model accuracy after I wrote this topic, the model with the pre-training weights did not tend to be more versatile. I’m sorry I jumped to conclusions.
I might think it’s a basic question,Are there any indicators for using pretrain weights? For example, it is effective for organs with low density, such as the lungs. etc.
Also , The pre-train I am using now is “resnet50_weights_tf_dim_ordering_tf_kernels.h5”, but do you have a pre-train-weight-file suitable for organ segmentation?