Real-time Visual Analysis of Microvascular Blood Flow for Critical...

3
Real-time Visual Analysis of Microvascular Blood Flow for Critical Care Chao Liu * Hernando Gomez Srinivasa Narasimhan * Artur Dubrawski * Michael R. Pinsky Brian Zuckerbraun 1. Blood flow velocity distributions for all pigs In the paper we have shown the blood flow velocity dis- tributions for 5 pigs in Fig. 7. In this section we show the blood flow velocity distributions for all of the 18 pigs in our critical care experiment in Fig. 1 and Fig. 2. From the point of view of current knowledge of physiology of the observed processes, as the blood pressure decreases due to bleeding, a general reduction in blood flow velocity would be mani- fest by a shift of the distribution of velocities across vessels towards lower values. On the other hand, one would expect that if resuscitation efforts were successful, that microcircu- latory blood flow return to baseline values. In the experiment, some of the subjects (pigs 42, 55, 57, and 63) experienced episodes of profound cardio- respiratory insufficiency before reaching the last stage of the experiment (AfterHextend), which substantially changed their observed behavior. Also, some of the subjects were apparently less responsive to Hextend therapy during resus- citation as their blood flow velocity did not increase right after infusion. 2. Performance of the vessel skeleton extrac- tion method To evaluate the performance of the vessel extraction method used in our paper, we manually segmented vessels in the microcirculatory videos and compared the result with the estimated vessel skeletons. In Fig. 3 we show three such comparisons. The averaged recall and false detection rates are 87.90% and 0.65% respectively. Please note that neither of the methods being compared is guaranteed to provide the ground truth. The comparison metrics aim to reflect the ex- tend of correspondence between the results of the laborious manual and fully automated process of segmentation. 3. Estimate the dominant orientation Let w(f x ,f y ) be the magnitude of the Fourier Trans- form, we want to find the optimal angle θ, the angle spanned * Carnegie Mellon University, The Robotics Institute. Email:{chao.liu, srinivas, awd}@cs.cmu.edu University of Pittsburgh, School of Medicine. Email:{gomezh, pin- skymr, zuckerbraunbs}@upmc.edu Figure 3: Three examples of comparisons between the au- tomatically detected vessel skeletons (blue) and the man- ually marked vessel segments (shown in gray with bright parts when they overlap). Manually identified skeletons are shown in red. Best viewed when zoomed in. by l and the y-axis, that minimizes the inertia: E = (r(f x ,f y ; θ)) 2 w(f x ,f y )df x df y (1) where r(f x ,f y ; θ) is the vertical distance from (f x ,f y ) to l; w(f x ,f y ) is the magnitude of the Fourier Transform of the EPI image. It can be shown that the direction vector (sin (θ * ) , cos (θ * )) T for the optimal θ * is the eigenvector with the smaller eigenvalue of the matrix: M = f 2 x w(f x ,f y )df x df y f x f y w(f x ,f y )df x df y f x f y w(f x ,f y )df x df y f 2 y w(f x ,f y )df x df y (2) 1 978-1-4673-6964-0/15/$31.00 ©2015 IEEE

Transcript of Real-time Visual Analysis of Microvascular Blood Flow for Critical...

Page 1: Real-time Visual Analysis of Microvascular Blood Flow for Critical …openaccess.thecvf.com/content_cvpr_2015/supplemental/Liu... · 2017-03-30 · Real-time Visual Analysis of Microvascular

Real-time Visual Analysis of Microvascular Blood Flow for Critical Care

Chao Liu ∗ Hernando Gomez † Srinivasa Narasimhan ∗ Artur Dubrawski ∗

Michael R. Pinsky † Brian Zuckerbraun †

1. Blood flow velocity distributions for all pigs

In the paper we have shown the blood flow velocity dis-

tributions for 5 pigs in Fig. 7. In this section we show the

blood flow velocity distributions for all of the 18 pigs in our

critical care experiment in Fig. 1 and Fig. 2. From the point

of view of current knowledge of physiology of the observed

processes, as the blood pressure decreases due to bleeding,

a general reduction in blood flow velocity would be mani-

fest by a shift of the distribution of velocities across vessels

towards lower values. On the other hand, one would expect

that if resuscitation efforts were successful, that microcircu-

latory blood flow return to baseline values.

In the experiment, some of the subjects (pigs 42, 55,

57, and 63) experienced episodes of profound cardio-

respiratory insufficiency before reaching the last stage of the

experiment (AfterHextend), which substantially changed

their observed behavior. Also, some of the subjects were

apparently less responsive to Hextend therapy during resus-

citation as their blood flow velocity did not increase right

after infusion.

2. Performance of the vessel skeleton extrac-

tion method

To evaluate the performance of the vessel extraction

method used in our paper, we manually segmented vessels

in the microcirculatory videos and compared the result with

the estimated vessel skeletons. In Fig. 3 we show three such

comparisons. The averaged recall and false detection rates

are 87.90% and 0.65% respectively. Please note that neither

of the methods being compared is guaranteed to provide the

ground truth. The comparison metrics aim to reflect the ex-

tend of correspondence between the results of the laborious

manual and fully automated process of segmentation.

3. Estimate the dominant orientation

Let w(fx, fy) be the magnitude of the Fourier Trans-

form, we want to find the optimal angle θ, the angle spanned

∗Carnegie Mellon University, The Robotics Institute. Email:{chao.liu,

srinivas, awd}@cs.cmu.edu†University of Pittsburgh, School of Medicine. Email:{gomezh, pin-

skymr, zuckerbraunbs}@upmc.edu

Figure 3: Three examples of comparisons between the au-

tomatically detected vessel skeletons (blue) and the man-

ually marked vessel segments (shown in gray with bright

parts when they overlap). Manually identified skeletons are

shown in red. Best viewed when zoomed in.

by l and the y-axis, that minimizes the inertia:

E =

∫∫

(r(fx, fy; θ))2w(fx, fy)dfxdfy (1)

where r(fx, fy; θ) is the vertical distance from (fx, fy)to l; w(fx, fy) is the magnitude of the Fourier Transform

of the EPI image. It can be shown that the direction vector

(sin (θ∗) , cos (θ∗))T

for the optimal θ∗ is the eigenvector

with the smaller eigenvalue of the matrix:

M =

[ ∫∫

f2

xw(fx, fy)dfxdfy∫∫

fxfyw(fx, fy)dfxdfy∫∫

fxfyw(fx, fy)dfxdfy∫∫

f2

yw(fx, fy)dfxdfy

]

(2)

1

978-1-4673-6964-0/15/$31.00 ©2015 IEEE

Page 2: Real-time Visual Analysis of Microvascular Blood Flow for Critical …openaccess.thecvf.com/content_cvpr_2015/supplemental/Liu... · 2017-03-30 · Real-time Visual Analysis of Microvascular

Pig 44

Pig 42

Pig 45

Pig 47

Pig 48

Pig 49

Pig 50

Pig 51

Pig 52

Pig 53

Dis

trib

ution d

ensity

Dis

trib

ution d

ensity

Dis

trib

ution d

ensity

Dis

trib

ution d

ensity

Dis

trib

ution d

ensity

Dis

trib

ution d

ensity

Dis

trib

ution d

ensity

Dis

trib

ution d

ensity

Dis

trib

ution d

ensity

Dis

trib

ution d

ensity

Blood flow velocity

distribution at three stages Blood flow velocity distribution

at all six stages

Blood flow velocity

distribution at three stages Blood flow velocity distribution

at all six stages

Figure 1: The estimated blood flow velocity distributions for pigs at different stages of the experiment. For each plot, the

x-axis is the blood flow velocity, (pixels per frame); the y-axis is the distribution density of vessels with corresponding flow

velocity. (a) The blood flow velocity distributions at three key stages: Baseline, end of bleed, and right after resuscitation.

(b) The blood flow velocity distributions for all six stages. Annotations for stages: Baseline (blue) - right before the bleeding

procedure; EndBleed (red) - end of bleed; Afterbleed (green) - 60 minutes after EndBleed; BeforeResusc (black) - Before

resuscitation, 90 minutes after EndBleed, before the resuscitation procedure; EndHextend (purple) - end of resuscitation

procedure; AfterHextend (yellow) - 120 minutes after EndHextend. The blood flow velocity decreases after the onset of

bleeding.

Page 3: Real-time Visual Analysis of Microvascular Blood Flow for Critical …openaccess.thecvf.com/content_cvpr_2015/supplemental/Liu... · 2017-03-30 · Real-time Visual Analysis of Microvascular

Blood flow velocity

distribution at three stages Blood flow velocity distribution

at all six stages

Dis

trib

ution d

ensity

Dis

trib

ution d

ensity

Dis

trib

ution d

ensity

Dis

trib

ution d

ensity

Dis

trib

ution d

ensity

Dis

trib

ution d

ensity

Dis

trib

ution d

ensity

Dis

trib

ution d

ensity

Blood flow velocity

distribution at three stages Blood flow velocity distribution

at all six stages

Pig 54

Pig 55

Pig 57

Pig 58

Pig 59

Pig 60

Pig 63

Pig 61

Figure 2: The estimated blood flow velocity distributions for pigs at different stages of the experiment (continued).