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Approved-By: [log in to unmask] References: <[log in to unmask]> Content-Type: text/plain; charset=US-ASCII; delsp=yes; format=flowed Message-ID: <[log in to unmask]> Date: Mon, 10 Dec 2007 10:02:41 +0000 Reply-To: ImageJ Interest Group <[log in to unmask]> Sender: ImageJ Interest Group <[log in to unmask]> From: Richard Han <[log in to unmask]> Subject: Re: k-means Clustering Comments: To: [log in to unmask] In-Reply-To: <[log in to unmask]>Hi Toby, Thank you so much for your reply. I would like to measure the area of red/blue from RGB images of histological slides. I have tried the Threshold color (HSV) as suggested to me by Jacqui Ross. It seems the Threshold color is very accurate (better than the k-means). If I use RGB split, the red channel actually resemble the blue in the original image?? I guess I will stick with the threshold color (HSV) for measurement. Regards Richard > > Date: Fri, 7 Dec 2007 10:31:32 -0500 > From: Toby Cornish <[log in to unmask]> > Subject: Re: k-means Clustering > > It might be helpful to know what sort of images these are. > > I haven't worked a lot with k-means for color discrimination, but > AFAIK this is just using kmeans clustering based on pixel RGB value > distances, so it doesn't really know "blue." You could follow up > the kmeans with a little algorithm that looks at the pixels in each > cluster and evaluates which cluster is the most red and which is > the most blue. > > Alternatively, you could use other means of segmenting an image > into colors, such as HSV colorspace segmentation. > > toby > >> Date: Thu, 6 Dec 2007 09:53:04 +0000 >> From: Richard Han <[log in to unmask]> >> Subject: k-means Clustering >> >> Dear All, >> >> I am using k-means Clustering to measure the blue and red in my >> images. I use the threshold to move from one cluster to another. In >> some images the k-means clustering could produce very good matches >> (I'd say spot on), but in others the results were less desirable. My >> settings are >> >> Number of clusters to: 4 >> Cluster center tolerance: 0.0001 >> Enable randomization seed: ticked >> Randomization seed: 48 >> The other options were not ticked >> >> Could I do anything more to improve the analysis? and... Is it >> possible to pre-define the red and blue clusters (ie, assign cluster >> 1 to be blue)? >> >> Any help will be appreciated. Thanking you. >> >> Richard Han >> University of Edinburgh > > > Toby C. Cornish, M.D., Ph.D. > Pathology Resident > Johns Hopkins Medical Institutions > [log in to unmask] > > ------------------------------ > > Date: Fri, 7 Dec 2007 10:48:08 -0500 > From: Toby Cornish <[log in to unmask]> > Subject: Re: k-means Clustering > > Something else I forgot is that you could try kmeans after > conversion from RGB colorspace to the LAB or another colorspace > (convert to a 3-slice stack in a new colorspace and run kmeans on > the stack). Plugins are readily available for that process. > > toby > >> Date: Thu, 6 Dec 2007 09:53:04 +0000 >> From: Richard Han <[log in to unmask]> >> Subject: k-means Clustering >> >> Dear All, >> >> I am using k-means Clustering to measure the blue and red in my >> images. I use the threshold to move from one cluster to another. In >> some images the k-means clustering could produce very good matches >> (I'd say spot on), but in others the results were less desirable. My >> settings are >> >> Number of clusters to: 4 >> Cluster center tolerance: 0.0001 >> Enable randomization seed: ticked >> Randomization seed: 48 >> The other options were not ticked >> >> Could I do anything more to improve the analysis? and... Is it >> possible to pre-define the red and blue clusters (ie, assign cluster >> 1 to be blue)? >> >> Any help will be appreciated. Thanking you. >> >> Richard Han >> University of Edinburgh > > > Toby C. Cornish, M.D., Ph.D. > Pathology Resident > Johns Hopkins Medical Institutions > [log in to unmask] > >
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