Using the Sonification for Hardly Detectable Details in Medical Images

Chiroiu, Veturia; Munteanu, Ligia; Ioan, Rodica; Dragne, Ciprian; Rugina, Cristian; Majercsik, Luciana

doi:10.29322/ijsrp.9.07.2019.p9146

Cited by 2 publications

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“…Optimization is required to modify the needle trajectory in order to protect the liver [17,18], to manage the tumor risk [19], and to change the robot architecture [20][21][22]. The inverse sonification problem for capturing hardly detectable details in a medical image is treated in [23], and the control in [24][25][26][27]. Microscopic investigation of the human liver offers details on its microanatomy with emphases to the granular, fibrillar components and irregular solid-fluid interfaces [28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Modeling of the Flexible Needle Insertion into the Human Liver

Chiroiu¹,

Munteanu²,

Rugina³

et al. 2021

Biomedical Signal and Image Processing

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The insertion of the needle is difficult because the deformation and displacement of the organs are the key elements in the surgical act. Liver and tumor modeling are essential in the development of the needle insertion model. The role of the needle is to deliver into the tumor an active chemotherapeutic agent. We describe in this chapter the deformation of the needle during its insertion into the human liver in the context of surgery simulation of the high- robotic-assisted intraoperative treatment of liver tumors based on the integrated imaging-molecular diagnosis. The needle is a bee barbed type modeled as a flexible thread within the framework of the Cosserat (micropolar) elasticity theory.

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Section: Introductionmentioning

confidence: 99%

Modeling of the Flexible Needle Insertion into the Human Liver

Chiroiu¹,

Munteanu²,

Rugina³

et al. 2021

Biomedical Signal and Image Processing

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Using the Sonification for Hardly Detectable Details in Medical Images

Chiroiu

Munteanu

Ioan

et al. 2019

Sci Rep

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The inverse sonification problem is investigated in this article in order to detect hardly capturing details in a medical image. The direct problem consists in converting the image data into sound signals by a transformation which involves three steps - data, acoustics parameters and sound representations. The inverse problem is reversing back the sound signals into image data. By using the known sonification operator, the inverse approach does not bring any gain in the sonified medical imaging. The replication of the image already known does not help the diagnosis and surgical operation. In order to bring gains in the medical imaging, a new sonification operator is advanced in this paper, by using the Burgers equation of sound propagation. The sonified medical imaging is useful in interpreting the medical imaging that, however powerful they may be, are never good enough to aid tumour surgery. The inverse approach is exercised on several medical images used to surgical operations.

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Using the Sonification for Hardly Detectable Details in Medical Images

Cited by 2 publications

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Modeling of the Flexible Needle Insertion into the Human Liver

Modeling of the Flexible Needle Insertion into the Human Liver

Using the Sonification for Hardly Detectable Details in Medical Images

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