DSI-Studio
DSI-Studio copied to clipboard
frankyeh
Neighbor correlation logic
Hi @frankyeh,
I was looking at this code with @mattcieslak
https://github.com/frankyeh/DSI-Studio/blob/8b5b13c2e5e05b83d5ebe8a8234cc715e66242a2/libs/dsi/image_model.cpp#L438C1-L482C2
with a view to implementing the DWI neighbor correlation in Python for inclusion in MRIQC. I am having a little trouble understanding the pairing logic
std::vector<std::pair<size_t,size_t> > corr_pairs;
for(size_t i = 0;i < src_bvalues.size();++i)
{
if(src_bvalues[i] == 0.0f)
continue;
float min_dis = std::numeric_limits<float>::max();
size_t min_j = 0;
for(size_t j = i+1;j < src_bvalues.size();++j)
{
tipl::vector<3> v1(src_bvectors[i]),v2(src_bvectors[j]);
v1 *= std::sqrt(src_bvalues[i]);
v2 *= std::sqrt(src_bvalues[j]);
float dis = std::min<float>(float((v1-v2).length()),
float((v1+v2).length()));
if(dis < min_dis)
{
min_dis = dis;
min_j = j;
}
}
corr_pairs.push_back(std::make_pair(i,min_j));
This seems to make two pairs for each pair (i,j), considering only candidate pairs j > i. So for i=0, vector src_bvectors[i] will be compared to vectors j in the range (1,src_bvalues.size()). So we may find a pair (0,a) where a > 0. But when a=i, we will compare vectors j in the range (a+1, src_bvalues.size()). So it will be paired with some other vector.
I feel like I'm missing something here, because it seems that as i increases, we are picking pairs from an increasingly small pool of candidates. It also seems to that I would get different pairs if I shuffled the acquisition order of the bvals and bvecs.
Apologies if I've got this totally wrong!
You do make a good point! This implementation may give a false underestimate of the neighboring DWI correlation. My mistake. I am correcting it now.
On Wed, Mar 27, 2024 at 10:20 AM Philip Cook @.***> wrote:
Hi @frankyeh https://github.com/frankyeh,
I was looking at this code with @mattcieslak https://github.com/mattcieslak
https://github.com/frankyeh/DSI-Studio/blob/8b5b13c2e5e05b83d5ebe8a8234cc715e66242a2/libs/dsi/image_model.cpp#L438C1-L482C2
with a view to implementing the DWI neighbor correlation in Python for inclusion in MRIQC. I am having a little trouble understanding the pairing logic
std::vector<std::pair<size_t,size_t> > corr_pairs; for(size_t i = 0;i < src_bvalues.size();++i) { if(src_bvalues[i] == 0.0f) continue; float min_dis = std::numeric_limits<float>::max(); size_t min_j = 0; for(size_t j = i+1;j < src_bvalues.size();++j) { tipl::vector<3> v1(src_bvectors[i]),v2(src_bvectors[j]); v1 *= std::sqrt(src_bvalues[i]); v2 *= std::sqrt(src_bvalues[j]); float dis = std::min<float>(float((v1-v2).length()), float((v1+v2).length())); if(dis < min_dis) { min_dis = dis; min_j = j; } } corr_pairs.push_back(std::make_pair(i,min_j));This seems to make two pairs for each pair (i,j), considering only candidate pairs j > i. So for i=0, vector src_bvectors[i] will be compared to vectors j in the range (1,src_bvalues.size()). So we may find a pair (0,a) where a > 0. But when a=i, we will compare vectors j in the range (a+1, src_bvalues.size()). So it will be paired with some other vector.
I feel like I'm missing something here, because it seems that as i increases, we are picking pairs from an increasingly small pool of candidates. It also seems to that I would get different pairs if I shuffled the acquisition order of the bvals and bvecs.
Apologies if I've got this totally wrong!
— Reply to this email directly, view it on GitHub https://github.com/frankyeh/DSI-Studio/issues/84, or unsubscribe https://github.com/notifications/unsubscribe-auth/AACDI4LI7ASPQQOFR4IY4ULY2LIR7AVCNFSM6AAAAABFK7GY7OVHI2DSMVQWIX3LMV43ASLTON2WKOZSGIYTAOJTG43TQOA . You are receiving this because you were mentioned.Message ID: @.***>
Here's the commit to correct this issue: https://github.com/frankyeh/DSI-Studio/commit/3596f8ff81859dabc1d0e9165fd02014f6d338ef
I also remove the mask requirement and added other code to handle some exceptional conditions.
Thank you again for reporting this issue.
Hi Frank, thanks for the quick fix! I was wondering if it might be possible to include a masked and unmasked NDC? Without the mask it's likely that the size of the field of view will affect NDC
Good point. I am adding it now.
On Wed, Mar 27, 2024 at 10:55 AM Matt Cieslak @.***> wrote:
Hi Frank, thanks for the quick fix! I was wondering if it might be possible to include a masked and unmasked NDC? Without the mask it's likely that the size of the field of view will affect NDC
— Reply to this email directly, view it on GitHub, or unsubscribe. You are receiving this because you were mentioned.Message ID: @.***>
https://github.com/frankyeh/DSI-Studio/commit/9aeb41dfaeeaf0dc762ce4ffdcac788c5629bdf0 now both masked and unmasked version are reported in the QC
Here I am also testing new QC metrics for DWI contrast: https://github.com/frankyeh/DSI-Studio/commit/6c53317d0b21b525c06f440b48818efcab87eebc and https://github.com/frankyeh/DSI-Studio/commit/d2a06b5e58ef8c2b736e019ac999e7edf77fa152
It is defined as the ratio between neighboring DWI correlation and orthogonal DWI correlation (NDC/ODC). The "orthogonal DWI" is the DWI nearest to the orthogonal ring of an evaluating DWI in the q-space. It works for single-shell, multi-shell, and grid data.
Good DWI contrast will have a ratio value larger than 1.2
For DWI acquired with a very low b-value, the NDC will be very good, but the DWI contrast will be close to 1.
this is good to know, I am in QC mode right now and will be adding them
It is open to better suggestions. I am also testing using different data. Frank
On Wed, Mar 27, 2024 at 2:54 PM Matt Cieslak @.***> wrote:
this is good to know, I am in QC mode right now and will be adding them
— Reply to this email directly, view it on GitHub https://github.com/frankyeh/DSI-Studio/issues/84#issuecomment-2023716465, or unsubscribe https://github.com/notifications/unsubscribe-auth/AACDI4IBVM6IKYUEKS3MEQLY2MIWLAVCNFSM6AAAAABFK7GY7OVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDAMRTG4YTMNBWGU . You are receiving this because you were mentioned.Message ID: @.***>