Feature Request: Object Detection or Instance Segmentation

[imagej]

Feature Request: Object Detection or Instance Segmentation

[ctrueden]

In this particular image, it might be possible to use traditional signal intensity thresholding + watershed methods, but most images, including possibly the above, have enough edge cases such that traditional approaches don't work.

I would not give up so easily. That image and similar ones could probably be segmented using a traditional segmentation approach in a reasonable amount of time by someone with enough experience creating such workflows.

I would have welcomed a plugin for reliably predicting ROI. Would anyone be interested in writing an object detection plugin?

Fiji has a lot of options already, including both "traditional" algorithms as well as pixel-based classification via ML. See Category:Segmentation for the list of plugins. There is also a guide on how to automate segmentation. And there is also CellProfiler, whose primary purpose in life is to automate object detection and measurements on that sort of data.

That's not to say that a plugin built on top of that particular pretrained TensorFlow model wouldn't be a good addition to Fiji! As a starting point, I'd encourage you to model your plugin after the MicroscopeImageFocusQualityClassifier. Reuse the same code to download and cache your particular pretrained model on demand. Strip out the logic and parameters you don't need. Tweak the calls to the actual TensorFlow API to build/invoke the graph the way it needs to be done for your model. Happy to help overcome obstacles; just post questions on the Image.sc Forum.