Hi, there, I have quite similar questions, could give a look at my post please?
I’m a new user of ImageJ, and I’m interested in measuring and comparing the fluorescence intensity as part of a time course analysis on embryos at different developmental stages. For my experiments I have antibody-stained cells across a variety of conditions (wild-type vs. Knock out, developmental days etc.). I’ve read several ImageJ articles and forum posts about this topic, but I’m having difficulty connecting what I’ve read to create a “tailored” analysis protocol for my experiment. I’ve included a sample image below of the fluorescence I’m hoping to measure for each of the first 3 channels (ch 4 is my Hoechst). There are around 150 cells in each image. I’d like to count and measure the fluorescence intensity of each nuclei (which I am manually counting using cellcounter tool) in order to get an average intensity per cell. I have struggled having a good nuclear segmentation even when tried clearing my samples and changing acquisition parameters ( Z stack 5uM to 2uM) . My images are acquired with identical settings meaning exposure time, illumination setting, camera gain, etc. My images are currently in a .nd2 format, 16 bits, but can not upload them here in such format. I uploaded a sample using .tif.
Q1: I am not sure about the value I should use to represent my data. In brief, I open, substract background, despeckle, and set B&C prior to splitting channels and doing Max IP. Does this preprocessing have any influence somewhow in my Intensity measurements?
Q2: After generating a MaxIP of the merged 4 channels, I define the ROI for each nuclei of interest, I also define 5-10 ROI of the background. I export my results to an excel tablewhere I paste Area, IntDen, and RawIntDen as results per channel. According to Fiji tutorial, Integrated Density - Calculates and displays two values: “IntDen” (the product of Area and Mean Gray Value) and “RawIntDen” (the sum of the values of the pixels in the image or selection). Is it Okay to just use in a XY graph, Int Den vs Nuclei?
I am not sure If I should work with RawIntDen instead. I am actually working with the later but do not really understand the difference. I calculate using the averages (RawInt /Area)-(AvgRawIntCtrl/AvgAreaCtrl). Were the first terms (RawInt /Area), have to do with my nuclei of interest its respective area, and I substract the second (AvgRawIntCtrl/AvgAreaCtrl) that come from my Background control spots. Which method is the proper way of representing data?
Q3: My images are currently in a .nd2 format, 16bits, therefore my arbitraty units range between 86 and 16000. I’ve seen people having A.U ranging between 0-255 which I assume comes from converting to 8 bits image. Do I need to additionally convert my images 8-bit formats prior to analyzing them. Is this something that I would need to do to analyze my images? What purpose does converting the image to a different bit type serve?
Thank you in advance for your help!
Here I attached the metadata and one image for your reference.