Discovering Shortest Path between Points in Cerebrovascular System

Suran, Shweta; Pattanaik, Vishwajeet; Malathi, D.

doi:10.1145/2662117.2662122

Cited by 8 publications

(10 citation statements)

References 3 publications

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“…Related work by Suran et al [2014] or Shen et al [2020] used the Dijkstra algorithm for the distance optimized path search, whereas we chose A* combined with the Euclidean heuristic. A* is optimally efficient for any given consistent admissible heuristic, which means no other optimal algorithm that utilizes the same heuristic expands fewer nodes than A* (except possible tie-breaks) [Russell and Norvig, 2002].…”

Section: Discussionmentioning

confidence: 99%

“…Hence, the use of A* decreased the run time to 64 %. Furthermore, Suran et al [2014] applied their algorithm on a pixel basis. We instead applied the algorithm on the bifurcation level.…”

Section: Discussionmentioning

confidence: 99%

“…Path finding algorithms are commonly used in various kinds of applications. On cerebrovascular vessel trees, Suran et al [2014] performed path search based on MRI angiography data. They considered the binary skeleton of a vessel tree as a graph, where each white pixel represents one node of the graph.…”

Section: Pathway Searchmentioning

confidence: 99%

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An Algorithm for the Labeling and Interactive Visualization of the Cerebrovascular System of Ischemic Strokes

Thamm¹,

Jürgens²,

Taubmann³

et al. 2022

Preprint

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During the diagnosis of ischemic strokes, the Circle of Willis and its surrounding vessels are the arteries of interest. Their visualization in case of an acute stroke is often enabled by Computed Tomography Angiography (CTA). Still, the identification and analysis of the cerebral arteries remain time consuming in such scans due to a large number of peripheral vessels which may disturb the visual impression. In previous work we proposed VirtualDSA++, an algorithm designed to segment and label the cerebrovascular tree on CTA scans. Especially with stroke patients, labeling is a delicate procedure, as in the worst case whole hemispheres may not be present due to impeded perfusion. Hence, we extended the labeling mechanism for the cerebral arteries to identify occluded vessels. In the work at hand, we place the algorithm in a clinical context by evaluating the labeling and occlusion detection on stroke patients, where we have achieved labeling sensitivities comparable to other works between 92 % and 95 %. To the best of our knowledge, ours is the first work to address labeling and occlusion detection at once, whereby a sensitivity of 67 % and a specificity of 81 % were obtained for the latter. VirtualDSA++ also automatically segments and models the intracranial system, which we further used in a deep learning driven follow up work. We present the generic concept of iterative systematic search for pathways on all nodes of said model, which enables new interactive features. Exemplary, we derive in detail, firstly, the interactive planning of vascular interventions like the mechanical thrombectomy and secondly, the interactive suppression of vessel structures that are not of interest in diagnosing strokes (like veins). We discuss both features as well as further possibilities emerging from the proposed concept.

show abstract

Section: Discussionmentioning

confidence: 99%

“…Hence, the use of A* decreased the run time to 64 %. Furthermore, Suran et al [2014] applied their algorithm on a pixel basis. We instead applied the algorithm on the bifurcation level.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

An Algorithm for the Labeling and Interactive Visualization of the Cerebrovascular System of Ischemic Strokes

Thamm¹,

Jürgens²,

Taubmann³

et al. 2022

Preprint

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show abstract

“…A cerebrovascular accident or a brain attack is known as stroke [1]. A stroke, damages the brain by interrupting adequate blood supply.…”

Section: Strokementioning

confidence: 99%

“…Damage caused by stroke depends on which part of the brain has suffered harm, to what degree and how fast the blood supply is restored to the part of the brain [14]. There are different types of strokes like: ischaemic stroke (caused by blocked arteries), haemorrhagic stroke (caused due to bleeding in the brain) and transient ischaemic attack or, TIA (also referred to as mini stroke) [1].…”

Section: Strokementioning

confidence: 99%

Brain Imaging Procedures and Surgery Techniques: Past, Present and Future

Suran

Pattanaik

Singh

et al. 2017

IJBSBT

Self Cite

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An algorithm for the labeling and interactive visualization of the cerebrovascular system of ischemic strokes

Thamm

Juergens

Taubmann

et al. 2022

Biomed. Phys. Eng. Express

View full text Add to dashboard Cite

During the diagnosis of ischemic strokes, the Circle of Willis and its surrounding vessels are the arteries of interest. Their visualization in case of an acute stroke is often enabled by Computed Tomography Angiography (CTA). Still, the identification and analysis of the cerebral arteries remain time consuming in such scans due to a large number of peripheral vessels which may disturb the visual impression. We propose VirtualDSA++, an algorithm designed to segment and label the cerebrovascular tree on CTA scans. Especially with stroke patients, labeling is a delicate procedure, as in the worst case whole hemispheres may not be present due to impeded perfusion. Hence, we extended the labeling mechanism for the cerebral arteries to identify occluded vessels. In the work at hand, we place the algorithm in a clinical context by evaluating the labeling and occlusion detection on stroke patients, where we have achieved labeling sensitivities comparable to other works between 92% and 95%. To the best of our knowledge, ours is the first work to address labeling and occlusion detection at once, whereby a sensitivity of 67% and a specificity of 81% were obtained for the latter. VirtualDSA++ also automatically segments and models the intracranial system leading to further processing possibilities. We present the generic concept of iterative systematic search for pathways on all nodes of said model, which enables new interactive features. Exemplary, we derive in detail, firstly, the interactive planning of vascular interventions like the mechanical thrombectomy and secondly, the interactive suppression of vessel structures that are not of interest in diagnosing strokes (like veins). We discuss both features as well as further possibilities emerging from the proposed concept.

show abstract

Discovering Shortest Path between Points in Cerebrovascular System

Cited by 8 publications

References 3 publications

An Algorithm for the Labeling and Interactive Visualization of the Cerebrovascular System of Ischemic Strokes

An Algorithm for the Labeling and Interactive Visualization of the Cerebrovascular System of Ischemic Strokes

Brain Imaging Procedures and Surgery Techniques: Past, Present and Future

An algorithm for the labeling and interactive visualization of the cerebrovascular system of ischemic strokes

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