Computer-aided detection of simultaneous abdominal organ from CT images based on iterative watershed transform

Belgherbi, Aicha

doi:10.26415/2572-004x-vol1iss1p8-8

Cited by 4 publications

(3 citation statements)

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“…This designed framework is a substantial achievement towards more sophisticated CASA systems. Soft computing can be used to reduce problems and augment the number of CASA functionalities as it is done with other computer-assisted medical diagnosis (11,12,13,14,15,16,17,18,19). Debris and other fine detail can be investigated with the help of Super-Resolution (15.…”

Section: Discussionmentioning

confidence: 99%

Automatic Human Sperm Concentrartion in microscopic videos

2019

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Abstract Background: Human sperm cell counting analysis is of significant interest to biologists studying sperm function and to medical practitioners evaluating male infertility. Currently the analysis of this assessment is done manually by looking at the sperm samples through a phase-contrast microscope using expert knowledge to do a subjective judgement of the quality. Aims: to eliminate the subjective and error prone of the manual semen analysis and to avoid inter and intra-laboratory inconsistencies in semen analysis test results Methods: In this paper we introduce a technique for human sperm concentration. Its principle is based on the execution of three steps: The first step in unavoidable. It concerns the pretreatment of the human sperm microscopic videos which consists of a conversion of the RGB color space into the YCbCr space, the “Gaussian filtering” and the “discrete wavelet filtering”. The second step is devoted to the segmentation of the image into two classes: spermatozoas and the background. To achieve this, we used an edge detection technique “Sobel Contour detector”. The third step is to separate true sperm from false ones. It uses a machine learning technique of type decision trees that consist on two classes classification based on invariant characteristics that are the dimensions of the bounding ellipse of the spermatozoid head as well as its surface. Results: To test the robustness of our system, we compared our results with those performed manually by andrologists. After results analysis, we can conclude that our system brings a real improvement of precision as well as treatment time which make it might be useful for groups who intend to design new CASA systems. Conclusion: In this study, we designed and implemented a system for automatic concentration assessment based on machine learning method and image processing techniques.

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Section: Discussionmentioning

confidence: 99%

Automatic Human Sperm Concentrartion in microscopic videos

2019

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“…These objectives can be accomplished by means of the indexing, the use of cases retrieval, and the search refinement strategies [24,25]. Better databases will also allow healthcare professionals to build more intelligence representations of the data with more information per pixel or voxel as well as high-resolution models with the help of deep learning [28,29,30,31,32].…”

Section: Databasesmentioning

confidence: 99%

Health 4.0: Applications, Management, Technologies and Review

Estrela

Monteiro

França

et al. 2019

Mèd Technologies J.

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The Industry 4.0 Standard (I4S) employs technologies for automation and data exchange through cloud computing, Big Data (BD), Internet of Things (IoT), forms of wireless Internet, 5G technologies, cryptography, the use of semantic database (DB) design, Augmented Reality (AR) and Content-Based Image Retrieval (CBIR). Its healthcare extension is the so-called Health 4.0. This study informs about Health 4.0 and its potential to extend, virtualize and enable new healthcare-related processes (e.g., home care, finitude medicine, and personalized/remotely triggered pharmaceutical treatments) and transform them into services. In the future, these services will be able to virtualize multiple levels of care, connect devices, and move to Personalized Medicine (PM). The Health 4.0 Cyber-Physical System (HCPS) contains several types of computers, communications, storage, interfaces, biosensors, and bio-actuators. The HCPS paradigm permits observing processes from the real world, as well as monitoring patients before, during, and after surgical procedures using biosensors. Besides, HCPSs contain bio-actuators that accomplish the intended interventions along with other novel strategies to deploy PM. A biosensor detects some critical outer and inner patient conditions and sends these signals to a Decision-Making Unit (DMU). Mobile devices and wearables are present examples of gadgets containing biosensors. Once the DMU receives signals, they can be compared to the patient's medical history and, depending on the protocols, a set of measures to handle a given situation will follow. The part responsible for the implementation of the automated mitigation actions are the bio-actuators, which can vary from a buzzer to the remote-controlled release of some elements in a capsule inside the patient's body. Decentralizing health services is a challenge for the creation of health-related applications. Together, CBIR systems can enable access to information from multimedia and multimodality images, which can aid in patient diagnosis and medical decision-making. Currently, the National Health Service addresses the application of communication tools to patients and medical teams to intensify the transfer of treatments from the hospital to the home, without disruption in outpatient services. HCPS technologies share tools with remote servers, allowing data embedding and BD analysis and permit easy integration of healthcare professionals' expertise with intelligent devices. However, it is undeniable the need for improvements, multidisciplinary discussions, strong laws/protocols, inventories about the impact of novel techniques on patients/caregivers as well as rigorous tests of accuracy until reaching the level of automating any medical care technological initiative.

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“…However, it is better to enrich it with other features. Furthermore, privacy policies regarding due to the delicate nature of medical/healthcare information are Future developments will analyze solutions from other places and how they can be translated to Algeria [9,10,11,12]. Moreover, provisions for intelligent mation retrieval and database handling must be thought [13,14].…”

Section: Emote Interaction Between a Physician And Patientmentioning

confidence: 99%

Designing and Implementing a Telemedicine System

Sebaa

Atroune

Chefai

et al. 2019

Mèd Technologies J.

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Background: A modern Teleconsultation System (TCS) improves patients' monitoring and favors remote assistance in terms of facilitating the daily life to the patients. This work investigates how to design and implement a modern remote consultation system. Methods: To achieve this work, we identify the actors who interact with the system to be developed and the use cases relating to each actor. A class model is designed to derive the relational model and the corresponding database. During implementation, we have used PHP language and MySQL database system. Results: A tele-consultation framework is implemented. The users (patients and doctors) must register then authenticate in order to use the system. The latter allows them audio and video conversation between them. Conclusion:We have given in this study how to design and implement a telemedicine system, which will improve health care, ensure continuity and quality of homecare while inhibiting intercurrences or complications, which will limit hospital admissions and limit medical travel.

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Computer-aided detection of simultaneous abdominal organ from CT images based on iterative watershed transform

Cited by 4 publications

References 0 publications

Automatic Human Sperm Concentrartion in microscopic videos

Automatic Human Sperm Concentrartion in microscopic videos

Health 4.0: Applications, Management, Technologies and Review

Designing and Implementing a Telemedicine System

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